- Create automated monitoring, auditing and alerting processes that ensure data quality and consistency.
- Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models
- Design, develop, implement, and optimize existing ETL processes that merge data from disparate sources for consumption by data analysts, business owners, and customers
- Seek ways to continually improve the operations, monitoring and performance of the data warehouse
- Influence and communicate with all levels of stakeholders including analysts, developers, business users, and executives.
- Live by and champion our values: #day-one, #ownership, #empathy, #humility.
What you’ll bring
- Typically, 5+ years experience in a data engineering related role (Data Engineer, Data Platform Engineer, Analytics Engineer etc) with a track record of building scalable data pipeline, transformation, and platform solutions.
- 3+ years of hands-on experience designing and building data pipelines and models to ingesting, transforming and delivery of large amounts of data, from multiple sources into a Dimensional (Star Schema) Data Warehouse, Data Lake.
- Experience with a variety of data warehouse, data lake and enterprise data management platforms (Snowflake {preferred}, Redshift, databricks, MySQL, Postgres, Oracle, RDS, AWS, GCP)
