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Data Engineer - Moonpig
Data Engineer
Data Engineer responsible for designing, building, and maintaining scalable data pipelines on AWS, leveraging Python, SQL, Airflow and Snowflake to enable real‑time analytics for a fast‑growing gift experience platform.
About the role
Key Responsibilities
- Design, develop, and optimise end‑to‑end data pipelines that ingest, transform, and load high‑volume transactional and event data.
- Implement and maintain workflow orchestration using Apache Airflow, ensuring reliable scheduling, monitoring, and alerting.
- Collaborate with data scientists, analysts, and product teams to translate business requirements into scalable data models in Snowflake.
- Write performant, production‑grade Python and SQL code for data extraction, transformation, and validation.
- Manage cloud infrastructure on AWS (S3, Redshift, Lambda, IAM) to support secure, cost‑effective data storage and processing.
- Monitor pipeline health, troubleshoot issues, and continuously improve data quality and latency.
Requirements
- 3+ years of hands‑on experience building data pipelines in a cloud environment, preferably AWS.
- Strong proficiency in Python and SQL, with a solid understanding of relational and columnar databases.
- Experience with workflow orchestration tools such as Apache Airflow or similar.
- Proven ability to work with modern data warehouses, especially Snowflake.
- Familiarity with ETL best practices, data modelling, and performance optimisation techniques.
Skills
pythonsqlsnowflakeaws