Director of Product Data Engineering & Analytics

Director of Product Data Engineering & Analytics is required by a global software company lead the design and delivery of data systems that capture and analyse product usage across a portfolio of software products.

Key responsibilities:

• Defining and implementing the data architecture for product telemetry across all products.
• Owning the design and evolution of the event data pipeline, from instrumentation through ingestion, transformation, and storage in a lakehouse environment
• Establishing and enforcing standards for event instrumentation (schemas, naming, versioning, required attributes)
• Designing and building reusable data assets, including curated datasets, semantic layers, and governed metrics
• Defining consistent data models for usage, engagement, and outcome measurement across products
• Developing and maintaining analytics and reporting capabilities for product teams
• Evaluating and selecting product analytics tools based on integration with the data platform, governance constraints, and cost
• Overseeing data ingestion pipelines and processing workflows to ensure reliability, data quality, and traceability
• Defining measurement frameworks and success metrics for product features and initiatives
• Building dashboards and analytical outputs used by product, engineering, and leadership teams
• Leading and growing a team of data engineers and product analysts

Required experience and skills

• Strong background in data engineering and large-scale data platform design
• Experience implementing event-based telemetry systems and instrumentation standards
• Experience defining product metrics, KPIs, and measurement frameworks
• Hands-on experience with Databricks (MLflow, Unity Catalog, or Feature Store is a plus)
• Strong SQL and Python skills
• Experience working across the full data lifecycle
• Experience leading and mentoring engineering or analytics teams
• Familiarity with product analytics tools and experimentation platforms
• Experience applying machine learning techniques to usage or behavioural data is beneficial