Associate Director, Enterprise Data Platforms

This is a fully remote position, open to applicants in Poland.

📋 Description

• Develop and implement a multi-year strategy and architecture for enterprise data and AI platforms.

• Create standards and reusable frameworks for data ingestion, integration, streaming, semantic layers, analytics, and AI workloads.

• Architect scalable, multi-domain platforms suitable for regulated operations across multiple regions.

• Lead governance for architecture, assess technological options, and make build-versus-buy decisions while managing vendor strategies, licensing, and partnerships.

• Integrate AI throughout the data lifecycle and establish enterprise patterns for AI-driven analytics, conversational BI, RAG, evaluation, observability, and responsible AI.

• Collaborate with domain leaders to transform AI and analytics pilot projects into secure and reusable enterprise capabilities.

• Manage platform FinOps responsibilities, including capacity planning, budget governance, cost transparency, showback/chargeback, workload policies, tagging, anomaly detection, and cost optimization.

• Oversee platform engineering and operational health, including architecture, access, infrastructure, CI/CD, observability, and disaster recovery.

• Provide platform-as-a-product features such as provisioning, onboarding, secure access, deployment templates, reusable frameworks, and self-service developer experiences.

• Apply SRE practices to ensure availability, performance, incident management, release management, disaster recovery, and production support.

• Ensure platforms comply with SOX, GxP, privacy, and data residency requirements across global operations.

• Establish observability for data products, pipelines, anomalies, incidents, and remediation ownership.

• Build and lead a global Data Platform Center of Excellence (CoE) or shared-services team.

• Define engagement models between centralized platform teams and federated domain data-product teams.

• Collaborate with senior executives and technical leaders to align platform strategy with business objectives.

• Facilitate communities of practice and foster talent development through standards, architecture forums, training, coaching, and hands-on technical leadership.

• Recruit, develop, and manage senior individual contributors and people managers; oversee the platform operating and capital budget.

⛳️ Requirements

• Over 10 years of experience in data platforms, data engineering, or enterprise data architecture, with at least 5 years in leadership roles involving teams and managers.

• Extensive architectural knowledge with Databricks, Azure data services, and medallion lakehouse architecture at an enterprise level.

• Strong experience in cloud architecture for Azure and AWS, including Infrastructure as Code (IaC), automation, and global multi-region deployment.

• Proven track record in delivering AI and GenAI platform capabilities, including AI/BI, semantic layers, conversational BI, MLOps/LLMOps, model serving, RAG, vector search, and agentic applications.

• Solid background in cloud FinOps and automation, focusing on cost optimization, governance, showback/chargeback, workload policy, and capacity management.

• Comprehensive experience managing an integrated data-platform ecosystem, including enterprise integration, MDM, data governance/cataloging, RPA, and related capabilities.

• Experience in a regulated industry, preferably in life sciences or pharmaceuticals, with understanding of GxP, validation, and data privacy requirements.

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.

• Strong communication and stakeholder-influence abilities across Infrastructure, Security, and business functions.

• Willingness to travel 10–15%, including occasional international trips.

🏝️ Benefits

• Equal opportunity employment.

• 10–15% travel, including occasional international travel.