Updated: 24 min read

10 IT Skills Worth Learning in 2026

What IT skills are most in-demand in 2026? A ranking of 10 technical competencies with the highest ROI - from AI/ML through cloud and Kubernetes to...

Łukasz Szymański Author: Łukasz Szymański

The IT market is changing at a pace that was unimaginable just 5 years ago. AI has become mainstream, cloud computing is no longer an option but a standard, and digital security is a matter of business survival. If you work in IT or plan to build a career in it, the question isn’t “should I develop myself?” but “what should I invest my time and energy in to get the greatest return?” In this article, we’ll analyze 10 IT competencies with the highest ROI in 2026 - those that will genuinely increase your value in the job market and open doors to better-paid roles.

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What IT skills are most valuable in 2026? AI/ML and prompt engineering, cloud architecture (AWS/Azure/GCP), Kubernetes, cybersecurity, DevOps/Platform Engineering, data engineering, Infrastructure as Code, API design, FinOps, and advanced Agile/Scrum.

How much more can I earn with these competencies? Depending on the skill: from 15% to 50% more than the market average. AI/ML and cloud architecture experts earn even 40-50% above baseline rates for developers.

How long will it take me to learn each skill? From 3 months (basic prompt engineering) to 12-18 months (advanced cloud architecture). The key is the “T-shaped skills” strategy - deep specialization + broad foundations.

Do I need to learn all skills at once? No. Start with 1-2 competencies related to your current role or career direction. T-shaped approach: first deepen your core skill, then expand horizontally.

Where can I learn these skills? Certified training (EITT), online platforms (Pluralsight, A Cloud Guru), vendor documentation (AWS, Microsoft, Google), hands-on projects, and community (conferences, meetups).

1. AI/ML and prompt engineering

Why is this important in 2026?

AI has ceased being a niche technology for data scientists and entered the business mainstream. Every medium-sized company and larger is either already implementing AI solutions or planning to do so in the coming quarters. The problem? There’s a shortage of specialists who can effectively utilize these technologies.

In 2026, the ability to work with LLMs (Large Language Models), understanding machine learning basics, and proficiency in prompt engineering is no longer “nice to have” but a baseline for many IT roles. Companies need people who can integrate OpenAI, Anthropic, or Google APIs into existing systems, optimize token costs, design effective prompts for specific use cases, and evaluate when AI is a good solution and when it’s overkill.

Salary premium: +40-50%

AI/ML specialists with 2-3 years of experience earn an average of 40-50% more than their peers in traditional backend roles. In Poland, rates for AI Engineers range from 20,000 to 35,000 PLN net on B2B, and for Machine Learning Engineers with experience in production systems - even more.

How to learn this?

Timeline: 6-12 months (depending on starting point)

  1. Fundamentals (2-3 months): Mathematics for ML (linear algebra, probability), Python (NumPy, Pandas), statistics basics. Courses: Fast.ai, Coursera Machine Learning Specialization.

  2. Practical ML (3-4 months): Scikit-learn, TensorFlow/PyTorch basics, classic ML algorithms (regression, classification, clustering), feature engineering. Projects: Kaggle competitions.

  3. LLM and prompt engineering (2-3 months): OpenAI API, Anthropic Claude, LangChain, RAG (Retrieval-Augmented Generation), fine-tuning basics, cost optimization. Hands-on: build a chatbot or AI assistant for a specific use case.

  4. Production ML (ongoing): MLOps, model deployment (Docker, Kubernetes), monitoring, A/B testing, ethical AI.

EITT training:

2. Cloud Architecture (AWS/Azure/GCP)

Why is this important in 2026?

Cloud computing is no longer a trend but a standard. According to Gartner’s report, over 85% of companies have moved or plan to move most workloads to the cloud by the end of 2026. The problem: migrating to the cloud is one thing, but effectively utilizing cloud capabilities is another.

Companies need cloud architects who understand not only technical aspects (compute, storage, networking, security) but also business implications of architectural decisions. Someone who can design scalable, secure, and cost-effective solutions is worth their weight in gold.

What’s important: cloud architecture isn’t just “knowing AWS/Azure/GCP services.” It’s the ability to design systems according to well-architected frameworks, understanding trade-offs between different approaches, knowledge of migration patterns, and capability to evaluate which workloads benefit most from cloud.

Salary premium: +35-45%

Cloud Architects in Poland earn an average of 25,000-40,000 PLN net on B2B, depending on experience and specialization (AWS, Azure, GCP, multi-cloud). This is 35-45% more than the average for senior developers without cloud expertise.

How to learn this?

Timeline: 12-18 months (to Solutions Architect level)

  1. Cloud fundamentals (3-4 months): Networking basics (TCP/IP, DNS, load balancing), Linux administration, security basics. Choose one cloud provider (AWS most popular, Azure strong in enterprise, GCP good for data/ML).

  2. Core services (3-4 months): Compute (EC2, Lambda), Storage (S3, EBS), Databases (RDS, DynamoDB), Networking (VPC, Security Groups), IAM. Hands-on: deploy a simple 3-tier application in the cloud.

  3. Advanced architecture (4-6 months): Well-Architected Framework, microservices patterns, serverless architecture, event-driven design, cost optimization, disaster recovery. Certifications: AWS Solutions Architect Associate, Azure Solutions Architect Expert.

  4. Specializations (ongoing): Multi-cloud, hybrid cloud, cloud security, FinOps, cloud-native development.

EITT training:

3. Kubernetes and containerization

Why is this important in 2026?

Kubernetes won the “container orchestration wars” and became the de facto standard for application deployment in cloud-native environments. In 2026, most new business applications are deployed on Kubernetes, and many legacy systems are undergoing migration to containers.

The problem: Kubernetes has a steep learning curve. Companies desperately need people who not only can “kubectl apply -f” but deeply understand K8s architecture, can debug production problems, optimize resource allocation, manage security, and implement observability.

Additionally: more and more companies are moving from “vanilla Kubernetes” to managed services (EKS, AKS, GKE) or platform abstracts (OpenShift, Rancher), so knowledge of the ecosystem around K8s is as important as knowledge of K8s itself.

Salary premium: +30-40%

Kubernetes Administrators and Platform Engineers earn an average of 22,000-35,000 PLN net on B2B. Experts with CKA/CKAD/CKS certification and 3+ years of production Kubernetes experience reach the upper ranges.

How to learn this?

Timeline: 6-9 months (to production-ready level)

  1. Containerization basics (1-2 months): Docker fundamentals, Docker Compose, container images, networking, volumes. Hands-on: containerize an existing application.

  2. Kubernetes core (3-4 months): Pods, Deployments, Services, ConfigMaps, Secrets, Namespaces, networking model, storage (PV/PVC), RBAC. Setup: local cluster (minikube/kind), then managed cluster (EKS/AKS/GKE).

  3. Production Kubernetes (2-3 months): Helm charts, monitoring (Prometheus, Grafana), logging (ELK, Loki), service mesh (Istio, Linkerd), CI/CD pipelines, autoscaling (HPA, VPA, cluster autoscaler), disaster recovery.

  4. Certifications: CKA (Certified Kubernetes Administrator), CKAD (Certified Kubernetes Application Developer), CKS (Certified Kubernetes Security Specialist).

EITT training:

4. Cybersecurity

Why is this important in 2026?

Cyber threats are growing exponentially - both in number and attack sophistication. In 2026, the average cost of a data breach for a company exceeds $4.5 million, and recovery time after a ransomware attack is weeks or months. Regulations (GDPR, NIS2, DORA) are becoming increasingly restrictive, and penalties for noncompliance - more severe.

The effect? Every company needs cybersecurity specialists. Not just dedicated security teams, but also developers and architects with solid security knowledge. Secure coding, threat modeling, penetration testing, incident response - these are skills that distinguish a good IT specialist from an average one.

What’s important: in 2026, cybersecurity isn’t just “protection from hackers.” It’s also privacy by design, secure supply chain, cloud security, IoT security, AI security (adversarial attacks, model poisoning). The field is broad, but the ROI - enormous.

Salary premium: +35-50%

Security Engineers, Penetration Testers, and Security Architects are among the best-paid roles in IT. Rates: 25,000-45,000 PLN net on B2B, depending on specialization and level. Ethical hackers with certifications (OSCP, CEH) and bug bounty portfolios reach the upper ranges.

How to learn this?

Timeline: 12-18 months (to Security Engineer level)

  1. Fundamentals (3-4 months): Networking (TCP/IP, routing, firewalls), Linux/Windows administration, scripting (Python, Bash), cryptography basics. Courses: CompTIA Security+, ethical hacking basics.

  2. Offensive security (4-6 months): Web application security (OWASP Top 10), network pentesting, exploitation techniques, Metasploit, Burp Suite. Practice: Hack The Box, TryHackMe. Certifications: CEH (Certified Ethical Hacker), OSCP (Offensive Security Certified Professional).

  3. Defensive security (4-6 months): SIEM (Splunk, ELK), incident response, forensics, malware analysis, threat intelligence. Certifications: CompTIA CySA+, GIAC (GCIH, GCIA).

  4. Specializations (ongoing): Cloud security (AWS/Azure/GCP security services), DevSecOps, application security, zero trust architecture.

EITT training:

5. DevOps/Platform Engineering

Why is this important in 2026?

DevOps has long ceased being a buzzword - it’s an established practice in most organizations. But in 2026, we see evolution: from “DevOps engineer who does everything” to specialized roles. One of the most sought-after: Platform Engineer.

Platform Engineering is a discipline of building internal developer platforms (IDPs) - tools and abstractions that enable developers to self-service deploy, monitor, and scale applications without deep infrastructure knowledge. Think: “Kubernetes as a Service” for your internal teams, but broader - CI/CD, observability, security, compliance, all in one cohesive ecosystem.

Companies invest in Platform Engineering because it increases developer productivity, reduces cognitive load, and accelerates time-to-market. But they need people who can design and build these platforms.

Salary premium: +30-40%

DevOps Engineers and Platform Engineers earn an average of 22,000-38,000 PLN net on B2B. Senior Platform Engineers in large organizations (fintech, e-commerce) reach the upper ranges.

How to learn this?

Timeline: 9-12 months (to mid-level)

  1. Fundamentals (3-4 months): Linux administration, scripting (Bash, Python), Git/GitHub, networking basics, cloud basics (AWS/Azure/GCP).

  2. CI/CD (2-3 months): Jenkins, GitLab CI, GitHub Actions, ArgoCD. Hands-on: build a pipeline from commit to production deployment.

  3. Infrastructure & orchestration (3-4 months): Docker, Kubernetes, Infrastructure as Code (Terraform), configuration management (Ansible). Integrate everything into a cohesive platform.

  4. Observability & reliability (2-3 months): Monitoring (Prometheus, Grafana), logging (ELK, Loki), tracing (Jaeger, Tempo), SRE practices (SLIs, SLOs, error budgets).

EITT training:

6. Data Engineering and analytics

Why is this important in 2026?

Data is the new oil - this saying from 2017, but in 2026 it’s more relevant than ever. Companies generate exploding amounts of data (IoT, mobile, web, internal systems), but many can’t effectively utilize this data. The problem isn’t the lack of data scientists or analysts, but the lack of solid data infrastructure.

This is where Data Engineers come in - specialists who build pipelines that ingest, transform, and deliver data in a reliable, scalable, and performant way. In 2026, this is one of the fastest-growing roles in IT because every data-driven initiative (AI, analytics, personalization, automation) starts with good data engineering.

What’s important: modern data engineering isn’t just ETL. It’s streaming data (Kafka, Flink), data lakes and lakehouses (Delta Lake, Iceberg), orchestration (Airflow, Dagster), data quality, governance, and lineage. The scope is broad, but the demand - enormous.

Salary premium: +35-45%

Data Engineers earn an average of 23,000-38,000 PLN net on B2B. Senior Data Engineers with experience in large-scale distributed systems (PB-scale data) reach the highest rates.

How to learn this?

Timeline: 9-12 months

  1. Fundamentals (3-4 months): SQL (advanced), Python (Pandas, PySpark), cloud basics (AWS/Azure/GCP), Linux/Bash, Git.

  2. Data pipelines (3-4 months): Apache Spark, Airflow/Dagster (orchestration), data warehouses (Snowflake, BigQuery, Redshift), ETL patterns. Hands-on: build an end-to-end pipeline (ingestion → transformation → serving).

  3. Advanced (3-4 months): Streaming (Kafka, Flink), data lakes (S3, Delta Lake), data modeling (Kimball vs. Inmon), data quality (Great Expectations), dbt (data build tool).

  4. Specializations (ongoing): Real-time analytics, ML engineering (MLOps), data governance.

EITT training:

7. Infrastructure as Code (Terraform)

Why is this important in 2026?

The days of manually clicking in AWS Console or Azure Portal are long gone - at least in organizations that take operations seriously. Infrastructure as Code (IaC) is the practice of defining and managing infrastructure through code, which brings the same benefits as version control for application code: reproducibility, auditability, collaboration, automation.

In 2026, Terraform (from HashiCorp) is the de facto standard for multi-cloud IaC. Companies use Terraform to provision everything: from VMs and networks, through Kubernetes clusters, to SaaS integrations (Datadog, PagerDuty, GitHub). If you work with infrastructure - cloud, on-prem, hybrid - knowledge of Terraform is a must-have.

What’s more: Terraform isn’t just “writing .tf files.” It’s understanding state management, modularization, testing (Terratest), security (tfsec, Checkov), collaboration (Terraform Cloud/Enterprise), drift detection. The scope of competencies is broader than it seems.

Salary premium: +25-35%

Infrastructure Engineers with Terraform expertise earn an average of 20,000-32,000 PLN net on B2B. Combined with cloud architecture or Platform Engineering - even more.

How to learn this?

Timeline: 4-6 months

  1. Basics (1-2 months): Terraform basics (providers, resources, data sources, variables, outputs), HCL syntax, state management. Hands-on: provision simple infrastructure (VPC, EC2, S3).

  2. Intermediate (2-3 months): Modules, workspaces, remote backends (S3, Terraform Cloud), provisioners, dynamic blocks. Best practices: DRY, separation of concerns, naming conventions.

  3. Advanced (1-2 months): Testing (Terratest), security scanning (tfsec, Checkov), CI/CD integration, policy as code (Sentinel, OPA), multi-account/multi-region setups.

  4. Certification: HashiCorp Certified: Terraform Associate.

EITT training:

8. API Design and integrations

Why is this important in 2026?

In the era of microservices, SaaS, and ecosystem integrations, every system is a composition of APIs. Good API design is the difference between a product that developers love and a product they hate. It’s also the difference between a system that scales effortlessly and a system that collapses under load.

In 2026, companies increasingly appreciate the value of well-designed APIs - both internal (for their own teams) and external (for customers and partners). They need people who understand not only technical aspects (REST vs GraphQL vs gRPC, authentication, rate limiting) but also developer experience, documentation, and API-first approach to product development.

What’s important: API design isn’t just “backend development.” It’s also API gateways (Kong, Apigee), service mesh (Istio), API management platforms, versioning strategies, backward compatibility, and deprecation policies.

Salary premium: +20-30%

Senior Backend Developers with specialization in API design and integrations earn an average of 20,000-30,000 PLN net on B2B. API Architects in large organizations - even more.

How to learn this?

Timeline: 6-9 months

  1. REST APIs (2-3 months): HTTP fundamentals, REST principles, status codes, authentication (OAuth 2.0, JWT), rate limiting, pagination. Hands-on: build a RESTful API (Node.js/Python/Java).

  2. Beyond REST (2-3 months): GraphQL (schema design, resolvers, federation), gRPC (protocol buffers, streaming), WebSockets (real-time communication). Evaluate: when to use which.

  3. API ecosystem (2-3 months): API gateways (Kong, AWS API Gateway), documentation (OpenAPI/Swagger), testing (Postman, REST Assured), observability (distributed tracing), security (OWASP API Top 10).

  4. Design principles: API-first development, versioning strategies, backward compatibility, error handling, idempotency.

EITT training:

9. FinOps / Cloud Cost Optimization

Why is this important in 2026?

Cloud brings enormous flexibility and scalability, but also… unexpectedly high bills. According to Flexera reports, an average of 30% of cloud spending is waste (unused resources, overprovisioning, inefficient architectures). In 2026, as more and more workloads migrate to the cloud, cost optimization becomes business-critical.

FinOps (Financial Operations) is an emerging discipline that combines finance, operations, and engineering to manage cloud spending in a data-driven way. It’s not about “saving at all costs,” but about balance between cost, performance, and innovation velocity.

Companies need FinOps practitioners - people who understand cloud pricing models, can analyze usage patterns, identify optimization opportunities, and implement governance policies. Combined with cloud architecture or DevOps skills, FinOps expertise dramatically increases your value.

Salary premium: +20-30%

FinOps Engineers and Cloud Cost Analysts earn an average of 18,000-28,000 PLN net on B2B. This is a relatively new role, so supply is low and demand - growing.

How to learn this?

Timeline: 4-6 months

  1. Cloud fundamentals (if you don’t have them): Basic AWS/Azure/GCP services, pricing models, billing dashboard.

  2. FinOps practices (2-3 months): Cost allocation (tagging, chargeback/showback), budgeting, forecasting, anomaly detection. Tools: AWS Cost Explorer, Azure Cost Management, CloudHealth, Kubecost.

  3. Optimization techniques (2-3 months): Right-sizing (compute, storage), commitment discounts (Reserved Instances, Savings Plans), spot instances, autoscaling, storage tiering, data transfer optimization.

  4. Governance & automation: Policy enforcement (AWS Service Control Policies, Azure Policy), automation (Lambda/Functions for cleanup), cost-aware CI/CD.

  5. Certification: FinOps Certified Practitioner (Linux Foundation).

EITT training:

10. Agile/Scrum (at advanced level)

Why is this important in 2026?

You might be surprised by the presence of Agile/Scrum in a ranking of technical skills. After all, it’s a “soft skill,” right? Not exactly. In 2026, mature Agile/Scrum knowledge - not “I participated in daily standup,” but deep understanding of principles, practices, and scaled frameworks - is a competitive advantage, especially for leadership roles (tech lead, engineering manager, architect).

Why? Because in large-scale software development, technical excellence isn’t enough. You need skills in facilitating collaboration, managing dependencies, aligning teams, delivering value incrementally, adapting to change. Agile/Scrum done right is a framework that enables this.

What’s more: in 2026, more and more companies are moving to scaled Agile frameworks (SAFe, LeSS, Scrum@Scale) for coordination across teams and value streams. Knowledge of these frameworks - especially combined with technical expertise - opens doors to senior IC roles and leadership positions.

Salary premium: +15-25%

Tech Leads, Scrum Masters, and Agile Coaches earn an average of 18,000-28,000 PLN net on B2B. Combined with deep technical expertise (e.g., Agile Coach with architecture background) - even more.

How to learn this?

Timeline: 6-9 months

  1. Fundamentals (1-2 months): Agile Manifesto, Scrum Guide, roles (Product Owner, Scrum Master, Dev Team), ceremonies (Sprint Planning, Daily, Review, Retro), artifacts (Product Backlog, Sprint Backlog, Increment).

  2. Practice (3-4 months): User stories and acceptance criteria, estimation (story points, planning poker), velocity tracking, definition of done, continuous improvement. Hands-on: facilitate ceremonies in your team.

  3. Advanced (2-3 months): Scaled frameworks (SAFe, LeSS), technical practices (TDD, CI/CD, pair programming), Agile metrics (cycle time, lead time, flow efficiency), Lean principles, Kanban.

  4. Certifications: Professional Scrum Master (PSM I/II), SAFe Agilist, PMI-ACP.

EITT training:

How to plan learning - “T-shaped skills” strategy

A ranking of 10 skills is one thing, but how to manage all this? After all, learning each of these competencies takes months of work. The answer: you don’t have to (and shouldn’t) learn everything at once. Instead: T-shaped skills strategy.

What are T-shaped skills?

It’s a metaphor of the letter “T” shape, where:

  • Vertical bar (depth): Your core expertise - one or two skills in which you’re an expert. This is your “specialization” - what you’re known for, what you do day-to-day, what distinguishes you in the market.
  • Horizontal bar (breadth): Broad understanding of many related skills. You don’t have to be an expert in them, but you understand the fundamentals, can talk with specialists, know when and how to apply them.

Why T-shaped?

Specialization without broader context leads to tunnel vision - you’re great in a narrow scope, but can’t collaborate effectively with other roles or understand the big picture. On the other hand, broad knowledge without depth leads to “jack of all trades, master of none” - you know a bit about everything, but nobody comes to you for expert advice.

A T-shaped professional is the sweet spot: deep enough for credibility and value delivery, broad enough for effective collaboration and career flexibility.

How to build your T-shape?

  1. Choose your vertical (1-2 skills): What interests you most? What’s most aligned with your current role or career aspiration? Start here. Go deep. Get certified, build a project portfolio, contribute to open source, write blogs, teach others.

    Examples:

    • Backend Developer → AI/ML + API Design
    • DevOps Engineer → Kubernetes + Terraform
    • Data Analyst → Data Engineering + Cloud Architecture

  2. Develop horizontal (3-4 related skills): Which skills often co-occur with your core? What skills do the people you collaborate with need? Learn enough to be dangerous - understand concepts, evaluate trade-offs, communicate effectively.

    Example for Backend Developer (core: AI/ML):

    • Horizontal: Cloud (AWS/Azure), Kubernetes (for ML deployment), DevOps (CI/CD for ML pipelines), Data Engineering basics (because ML needs data)

  3. Iterate and adjust: Your T-shape isn’t static. As your career develops, with market changes and your interests, you’ll pivot or deepen different areas. That’s fine. Keep learning.

Realistic timeline:

  • Year 1: Deep dive into 1 core skill (e.g., Kubernetes). You learn 10-15h/week, get certified, build projects. Simultaneously: basics of 2-3 horizontal skills (e.g., Terraform, Cloud, DevOps).
  • Year 2: Deepen core (production experience, advanced topics). Add 1 more core skill (e.g., Platform Engineering). Continue expanding horizontal.
  • Year 3+: Maintain and update core skills (new versions, emerging patterns). Selectively deepen selected horizontal skills based on career direction.

Key mindset: Learning is a continuous process, not a destination. Technologies change, best practices evolve, new skills emerge. Allocate 5-10h/week to learning - read blogs, watch conference talks, experiment with new tools, learn from projects at work.

How EITT helps build IT competencies

For over 20 years, EITT has supported Polish IT specialists in career development. Thanks to collaboration with over 500 experts and experience from 2,500+ conducted trainings, we offer comprehensive support in building T-shaped skills we wrote about above.

What distinguishes us?

  1. Certified training from top vendors: AWS, Microsoft Azure, Google Cloud, Kubernetes (Linux Foundation), HashiCorp, CompTIA, PMI. Our trainings prepare for official certifications that are recognized globally.

  2. Hands-on approach: Not just theory - every training includes extensive practice with real-world scenarios. Labs, case studies, projects - you learn by doing.

  3. Expert practitioners: Our trainers aren’t just certified instructors, but above all practitioners with active production experience. You learn from people who work daily with the technologies they teach.

  4. Flexible learning paths: We offer both intensive bootcamps (week full-time) and extended courses (weekends over several weeks) as well as online self-paced learning. Adapt the format to your lifestyle.

  5. Career guidance: Don’t know which certification to choose? What career path to take? Our advisors will help you define a learning path aligned with your goals.

Example development paths with EITT:

For Backend Developer → AI/ML Specialist:

  1. Python for Data Science (fundamentals)
  2. AWS Machine Learning - Specialty or Azure AI Fundamentals
  3. Kubernetes for Developers (CKAD) - for ML deployment
  4. MLOps / ML Engineering (advanced)

For IT Generalist → Cloud Architect:

  1. AWS Solutions Architect - Associate or Azure Administrator
  2. Kubernetes Fundamentals
  3. Terraform Associate
  4. AWS Solutions Architect - Professional (advanced)

For Developer → DevOps/Platform Engineer:

  1. Docker and Kubernetes Fundamentals
  2. DevOps Foundation
  3. Terraform Associate
  4. AWS DevOps Engineer - Professional or GitLab CI/CD

Corporate development programs:

Do you work in a company that invests in team development? EITT offers dedicated corporate programs:

  • Tailored curricula adapted to your tech stack and business needs
  • On-site or online delivery - you decide
  • Group discounts for larger teams
  • Post-training support - Q&A sessions, office hours with trainers

Average rating 4.8/5 from our training participants. Join thousands of IT specialists who developed their careers with EITT.

Check out our full training offer →

FAQ

Do I need to know all 10 skills to be competitive in the IT market in 2026?

No. The key is the T-shaped approach: deep specialization in 1-2 areas + broader understanding of several related skills. Nobody is an expert in everything, and trying to learn everything simultaneously leads to surface-level knowledge without depth. Choose 1-2 core skills aligned with your career goals and interests, go deep, then expand horizontal knowledge as needed.

How much time should I dedicate to learning weekly?

It depends on your ambitions and starting point. Minimum for continuous development: 5-7h/week. For aggressive upskilling (e.g., certification preparation): 10-15h/week for 3-6 months. Remember: learning is a marathon, not a sprint. Better 1h daily consistently than 10h on weekends once a month. Build habits, not heroic efforts.

Is it worth getting certifications, or is hands-on experience enough?

Both. Certifications have real value: (1) Structured learning path - they ensure you cover all fundamentals, not just pieces needed in your current project. (2) Signal in the market - recruiters and hiring managers use certifications as a filter. (3) Confidence - official confirmation of your competence. BUT: certification without hands-on experience is a red flag. Best approach: learn through projects (work, side projects, open source), and treat certification as formalization and validation of knowledge.

Which skills have the best ROI for someone at the beginning of an IT career?

For junior/mid-level: Cloud Architecture (AWS/Azure) + Kubernetes. Why? (1) High demand - most companies are migrating to cloud or are already there. (2) Broad applicability - cloud skills are relevant regardless of specialization (backend, DevOps, data, security). (3) Clear certification paths - AWS/Azure have well-established learning paths and certifications recognized globally. (4) Foundation for other skills - cloud is a gateway to Kubernetes, DevOps, FinOps, AI/ML infrastructure. Start here, then specialize based on interest.

Does knowledge of Agile/Scrum really increase earnings for technical roles?

Yes, especially for senior IC roles and tech leadership. Why? Because in large teams and organizations, delivering value isn’t just about code. It’s also coordination, stakeholder management, continuous improvement. A Tech Lead with deep Agile knowledge facilitates better collaboration, removes blockers, aligns work with business goals - this translates to better outcomes, which translates to better compensation. Plus: Agile/Scrum knowledge is a gateway to leadership roles (Engineering Manager, Product-Minded Engineer, Architect), where earnings are significantly higher than pure IC.

Summary: Your strategy for 2026

The IT market in 2026 offers unprecedented opportunities for those who consciously invest in competency development. Key takeaways:

  1. T-shaped skills: Specialize deeply in 1-2 areas, develop broadly in related skills.

  2. AI/ML, Cloud, and Kubernetes: Top 3 skills in terms of demand and salary premium. If you don’t know where to start - start here.

  3. Security and FinOps: Emerging areas with low supply and growing demand. Early movers have an advantage.

  4. Certifications + hands-on: Best results from combining structured learning (training, certifications) and practical experience (projects, work).

  5. Continuous learning: 5-10h/week allocated to learning is an investment with the highest long-term ROI in your career.

  6. Strategic learning path: Don’t learn chaotically. Define your T-shape, choose core skills, plan a learning path, execute consistently.

EITT supports you at every stage of this journey. From fundamentals (Python, Linux, networking) to advanced certifications (AWS Solutions Architect Professional, CKA, OSCP) - we have a proven track record in developing IT professionals’ careers in Poland.

Ready for the next step in your career?

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Your future in IT starts today. Choose the skills you’ll build in 2026 and start taking action.

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