[Hiring] Lead Data Engineer @vaga para Lead Data Engineer na Launch Potato

Role Description

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.

Qualifications

• 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.

Requirements

• 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

Competencies

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools.
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions.
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently.
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows.
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations.
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering.

Benefits

• Accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers.