remote
Analytics Engineer - Personalisation
Data Engineer
Build and maintain scalable data models and pipelines for personalisation initiatives, leveraging dbt, SQL, and modern ELT practices to deliver reliable, analytics‑ready data to downstream teams.
About the role
Key Responsibilities
- Design, develop, and optimise dbt models that power personalisation features across product and marketing platforms.
- Construct and maintain robust ELT pipelines, ensuring data quality, lineage, and timely delivery from source systems to the warehouse.
- Collaborate with data scientists, product analysts, and engineers to translate business requirements into scalable data models and analytical solutions.
- Implement best practices for data warehousing, including partitioning, indexing, and performance tuning to support high‑volume query workloads.
- Monitor, troubleshoot, and resolve data integrity issues, providing clear documentation and automated testing for all data assets.
Requirements
- 3+ years of experience building data models and pipelines using dbt and SQL in a cloud data warehouse (e.g., Snowflake, BigQuery, Redshift).
- Strong understanding of ELT concepts, data warehousing design patterns, and modern data stack tooling.
- Proficiency in writing performant SQL queries and creating reusable, well‑documented dbt transformations.
- Experience collaborating with cross‑functional teams to deliver data solutions that enable personalisation and analytics use cases.
- Solid problem‑solving skills, attention to data quality, and a passion for continuous improvement of data infrastructure.