engineering
Posted May 5Analytical Engineer f/m/d
at Contentful
London, United KingdomOn-site
Responsibilities
- 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.
- Develop reusable, maintainable data transformations that enable self-serve analytics in Tableau and other BI tools.
- Collaborate with data platform engineers to optimize performance, governance, and cost efficiency in Snowflake.
Requirements
- 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.
- 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 systems (e.g., Salesforce, Gainsight).
- Governance: Understanding of data cataloging, lineage, and documentation using tools like Atlan
- By blending composability with native AI capabilities, Contentful enables dynamic personalization, automated content delivery, and real-time experimentation, powering next-generation digital experiences across brands, regions, and channels for more than 4,200 organizations worldwide.
Experience
- Experience: 3+ years in analytics engineering, data engineering, or BI development in a modern data stack environment.