Head of Data Platforms

• 10+ years of experience in data platforms, data engineering, cloud data architecture, or a related domain.


• 5+ years of experience leading managers, senior engineers, architects, and global technical teams.


• Deep expertise in modern data platform architectures, including lakehouse and cloud-native data ecosystems.


• Hands-on experience with enterprise-scale cloud platforms, particularly Azure and/or AWS.


• Strong knowledge of Databricks or comparable large-scale analytics platforms.


• Experience delivering AI and GenAI platform capabilities, including MLOps, LLMOps, RAG, vector search, model serving, and AI-powered analytics.


• Strong background in Infrastructure as Code, automation, DevOps, and platform engineering.


• Proven success driving cloud FinOps, governance, cost optimization, and operational excellence initiatives.


• Familiarity with data governance, master data management, integration platforms, and enterprise data management practices.


• Experience operating within complex, highly regulated environments is highly desirable.


• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related discipline; advanced degree preferred.

The employer is a global biotechnology company focused on developing innovative therapies for serious diseases. It combines scientific research with advanced technology to deliver impactful treatments and improve patient outcomes worldwide.

Industry: Technology & Telecoms

Area: IT Data Analysis

Your responsibilities

Platform Strategy & Architecture

• Define and execute a multi-year vision and roadmap for enterprise data and AI platforms.


• Establish standards, frameworks, and best practices for data ingestion, integration, streaming, semantic models, analytics, and AI workloads.


• Design and evolve scalable platform architectures supporting multiple business domains and geographic regions.


• Lead architecture governance, technology assessments, and strategic platform investment decisions.


• Drive platform simplification initiatives by reducing tool fragmentation and technical debt.


• Manage strategic technology partnerships and vendor relationships.

AI & Advanced Analytics Enablement

• Leverage AI to improve metadata management, data quality, lineage, documentation, operational efficiency, and platform support.


• Define enterprise patterns for AI-enabled analytics, generative AI, conversational BI, retrieval-augmented generation (RAG), model observability, and responsible AI practices.


• Partner with business and technology stakeholders to scale successful AI initiatives into enterprise-wide capabilities.


• Maintain an innovation roadmap balancing business value, operational excellence, risk management, and regulatory requirements.

FinOps & Cost Optimization

• Own financial governance and cost efficiency across the data and AI platform landscape.


• Lead capacity planning, budget management, and cloud cost optimization initiatives.


• Establish cost transparency through chargeback/showback models, workload governance, and usage monitoring.


• Define measurable targets and KPIs for platform efficiency and value realization.

Engineering, Operations & Reliability

• Oversee platform engineering, cloud infrastructure, access management, automation, CI/CD, monitoring, and resilience.


• Deliver platform-as-a-product capabilities, including self-service provisioning, reusable frameworks, deployment templates, and developer enablement.


• Introduce and mature Site Reliability Engineering (SRE) practices covering availability, performance, incident response, capacity planning, and disaster recovery.


• Govern reusable accelerators, frameworks, and platform services as managed products with defined roadmaps and release plans.


• Ensure adherence to enterprise security, privacy, compliance, audit, and governance standards.


• Implement end-to-end observability for data products, pipelines, workloads, and operational health.

Leadership & Operating Model

• Build and lead a global team responsible for enterprise data and AI platform capabilities.


• Define effective engagement models between centralized platform organizations and distributed domain teams.


• Collaborate with senior business and technology leaders to align platform investments with strategic priorities.


• Foster communities of practice and drive adoption of platform standards and best practices.


• Develop technical talent through coaching, mentorship, architecture reviews, and capability-building initiatives.

What's on Offer

• Private medical care


• Annual bonus


• Employee stock purchase plan


• Flexible benefits budget


• Life insurance


• Hybrid work model (3 days in the office)


• Modern office in Warsaw

Requirements: Cloud, Cloud platform, Azure, AWS, Databricks, Analytics platform, AI, MLOps, Infrastructure as Code, DevOps, Data management, Degree Additionally: Private healthcare.