Product Data Engineering & Analytics Director
WifiRemoteexecutive
EngineeringProduct ManagementOtherData EngineeringAnalytics DirectorProduct Director
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Quick Summary
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,
Technical Tools
EngineeringProduct ManagementOtherData EngineeringAnalytics DirectorProduct Director
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
Location & Eligibility
Where is the job
Worldwide
Fully remote, anywhere in the world
Who can apply
Same as job location
About this job
- Posted
- 134 days ago
Listing Details
- First seen
- June 17, 2026
- Last seen
- October 29, 2026
Posting Health
- Days active
- 133
- Repost count
- 0
- Trust Level
- 40%
- Scored at
- October 29, 2026
Signal breakdown
freshnesssource trustcontent trustemployer trust
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