**Job Title: Senior Data / Analytics Engineer

Client Location: Canada

Work Location: Remote** **Work Schedule: Monday to Friday (9:30 PM to 6:30 AM IST)

Experience Level: 5+ Years** About The Role As our Senior Data / Analytics Engineer, you'll build and own the data foundation that powers our products, analytics, and AI capabilities. You'll be responsible for the systems that capture, organize, validate, and make our data usable, both for people and for machines.

This is a senior, product-minded engineering role. We're looking for someone who understands that a data pipeline isn't successful simply because it moves data from A to B. The data needs to be reliable, understandable, accessible, and structured in a way that can evolve as our products and AI capabilities evolve.

What You'll Do

- Own the core data foundation that captures and organizes behavioural and product data across our systems.
- Evaluate and recommend the platforms and services our data infrastructure should be built on, including an honest view of where buying a proven solution beats building our own.
- Design, build, and maintain production-grade behavioural data pipelines that reliably capture the signals our products and AI systems need.
- Develop data models and schemas that can evolve as our products, customer needs, and data requirements change.
- Model data so that comparisons stay valid over time — the same event can be measured against itself a year later without re-engineering the schema every season.
- Build systems that make our data accessible and useful to both internal teams and AI-powered applications.




- Establish and maintain a semantic layer that turns underlying data into meaningful, consistent concepts that can be understood and used by both internal teams, and AI systems.
- Treat data quality as an engineering discipline by implementing data contracts, automated testing, validation, monitoring, and alerting.
- Investigate and resolve data quality, pipeline, and instrumentation issues, including understanding the root cause of failures.
- Partner with product managers and engineering to determine what data needs to be captured and how it should be structured.
- Help establish standards and best practices for data instrumentation, modelling, quality, and accessibility.
- Design systems with reliability, scalability, privacy, and security in mind.
- Design and enforce strict client data isolation, so that one customer's data is never visible to another and aggregate insight can be produced without identifying individuals.
- Contribute to the technical direction of our data architecture as our AI and product capabilities evolve.

What We're Looking For

- Significant experience as a data or analytics engineer, with experience designing and operating production data systems.
- Demonstrated experience shipping a behavioural event pipeline into production and, importantly,



the ability to explain what went wrong, what you learned, and how you improved it.
- Solid experience with data modelling and designing schemas that can evolve without creating unnecessary downstream complexity.
- Experience with temporal data modelling — slowly changing dimensions, event versioning, or similar approaches for keeping historical comparisons valid as definitions change.
- Experience building reliable data pipelines and production data infrastructure.
- Experience designing multi-tenant data systems with hard isolation requirements.
- A strong understanding of data quality, including data contracts, automated tests, monitoring, and observability.
- Experience making data accessible and usable for analytics, applications, and/or AI systems.
- A product mindset—you think about who will use the data and what they need to accomplish, rather than treating data as an isolated technical problem.
- Sound build-versus-buy judgment, and a willingness to recommend buying — with the trade-offs written down — rather than defaulting to building it yourself.
- Strong software engineering fundamentals and an ability to write maintainable, reliable production code.
- Comfort working across product and engineering teams and translating business requirements into practical data solutions.
- Strong problem-solving skills and a willingness to dig into difficult data problems rather than simply working around them.
- Excellent communication skills and the ability to explain complex data concepts to both technical and non-technical stakeholders.

📌 Senior Data / Analytics Engineer (India)
🏢 Outsourced
📍 India