Analytics Engineer (9 month FTC)
Team: Data (Moonpig)
Location: London
Commitment: Maternity Cover
Workplace Type: hybrid
Key Responsibilities
- Build, optimise, and maintain robust data transformation pipelines using dbt and Snowflake.
- Translate business needs into well-structured data models that drive insights and decisions.
- Ensure data quality, reliability, and accessibility through automated testing, monitoring, and governance.
- Partner with BI, Data Science, and Engineering teams to deliver impactful data products.
- Govern and optimise the Snowflake data warehouse for performance, security, and cost-efficiency.
- Develop automated data tests, monitoring, and alerts using tools like Metaplane.
- Maintain clear documentation and promote best practices in analytics engineering.
- Evaluate and integrate emerging technologies (e.g., Dagster) to improve efficiency and scalability.
About you
- You have exceptional SQL skills for complex data manipulation and analysis.
- You’re highly skilled in dbt, designing and maintaining scalable transformation models.
- You have experience with Snowflake or other big data systems (e.g., BigQuery).
- You bring working knowledge of Python for automation and data integration.
- You thrive in an agile environment, balancing precision with timely delivery.
- You’re naturally curious, always seeking to enhance your technical capabilities.
- Bonus points if you also have:
- Experience with Metaplane or similar data monitoring tools.
- Familiarity with git for version control.
- Exposure to orchestration and ingestion tools such as Fivetran or Dagster.
- Understanding of data visualisation tools such as Tableau.
Our Tech Stack
- Data Stack: Snowflake, dbt, SQL, Python, Fivetran, Dagster, Metaplane, Tableau
- Infrastructure: AWS (SageMaker, EC2, Lambda, Glue, S3), Terraform, API Gateway
- Collaboration: GitHub, Jira, Confluence
- Analytics: GA4, GTM, GCP BigQuery
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