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Senior Data Engineer - Houseful
Data Engineer
Senior Data Engineer to design, build, and scale data pipelines and warehouses for property data services, leveraging Python, SQL, Airflow, Snowflake, AWS, and Spark to support analytics and AVM models.
About the role
Key Responsibilities
- Design, develop, and maintain robust ETL/ELT pipelines using Python, Apache Airflow, and Spark to ingest and transform large‑scale property data.
- Build and optimise data warehouse solutions on Snowflake, ensuring high performance, scalability, and data quality.
- Collaborate with product, analytics, and machine‑learning teams to deliver reliable data services that power valuation models and customer insights.
- Implement data governance, monitoring, and alerting frameworks on AWS to guarantee pipeline reliability and compliance.
- Mentor junior engineers, conduct code reviews, and champion best practices in data engineering and cloud architecture.
Requirements
- 5+ years of professional experience building data pipelines and warehouses in a cloud environment.
- Strong proficiency in Python, SQL, and data processing frameworks such as Spark.
- Hands‑on experience with Apache Airflow for workflow orchestration and Snowflake for data warehousing.
- Deep understanding of AWS services (e.g., S3, Redshift, Lambda, IAM) and infrastructure‑as‑code concepts.
- Proven ability to work cross‑functionally, solve complex data problems, and mentor team members.
Skills
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