Analytics Engineer
About the Role
We’re looking for an experienced Analytics Engineer to help build the next generation of Contentful’s analytics foundation, powering Insight 360, our unified Snowflake-based data platform.
In this role, you’ll design and maintain robust, scalable data models that make our business data accessible and actionable across all teams. You’ll collaborate with engineers, analysts, and business stakeholders to deliver high-quality, trusted datasets that enable data-driven decision-making across the company.
Your work will sit at the heart of Contentful’s data evolution, helping us move to a modern, governed, and insight-led architecture.
Key Responsibilities
Data Modeling & Transformation
- Design, build, and maintain efficient, scalable analytics models in dbt and Snowflake .
- Transform raw data from diverse domains (product, finance, sales, marketing, operations) into analytics-ready structures.
- Apply best practices in modularity, documentation, and testing to ensure long-term reliability.
Pipeline Ownership
- Take ownership of analytics engineering projects end-to-end: from scoping requirements through implementation and monitoring.
- Develop reusable, maintainable data transformations that enable self-serve analytics in Tableau and other BI tools.
Enablement & Collaboration
- Partner with analysts, data scientists, and business teams to define and deliver trusted data assets.
- Collaborate with data platform engineers to optimize performance, governance, and cost efficiency in Snowflake.
- Contribute to the shared data catalog and drive adoption of best practices across analytics and engineering teams.
What You’ll Need
Required
- Experience: 3+ years in analytics engineering, data engineering, or BI development in a modern data stack environment.
- Data Modeling: Proven expertise with SQL to build modular and well-documented data models in dbt. Understanding of various data modeling techniques.
- Warehouse Experience: Deep knowledge of Snowflake (warehouses, roles, virtual warehouses, performance tuning).
- Collaboration: Strong ability to work cross-functionally with analysts, engineers, and business stakeholders to translate needs into technical solutions.
- Data Ops: Experience applying version control, testing, and observability practices in dbt or similar frameworks.
Preferred
- Visualization: Experience structuring data for BI tools such as Tableau , focusing on scalability and performance.
- Ingestion & Orchestration: Familiarity with Airflow , or similar tools for data ingestion and orchestration.
- Reverse ETL: Working knowledge of tools like Hightouch for operationalizing insights back into business syste