Head of Data Platforms

Opis oferty

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

Wymagania

• 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.