Tech Stack

Description

You will lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data. Your work will involve building and optimizing ETL pipelines, managing data lake infrastructure, and ensuring data quality to support business intelligence and strategic growth.

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

Responsibilities

• Lead scalable data engineering efforts
• Build and optimize scalable, efficient ETL and data lake processes
• Own the ingestion, modeling, and transformation of structured and unstructured data
• Partner closely with BI and Analytics to deliver clean, query-ready datasets
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure
• Drive adoption and advancement of Looker dashboards
• Contribute to the future of Launch Potato’s data team by mentoring peers