Responsibilities
- Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.
- Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business.
- Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units.
- Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth.
- Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows.
- Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity.
- Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support.
- Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture.
Requirements
- 5+ years of experience in data engineering within fast-paced, cloud-native environments
- Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
- Experience building and managing scalable ETL pipelines and data lake infrastructure
- Familiarity with distributed systems, Spark, and data quality best practices
- Strong cross-functional collaboration skills to support BI, analytics, and engineering teams
- 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations
