Join our team as a Senior Data Engineer and build modern data infrastructure that powers self-service analytics and high-quality data products at scale. Design, build, and evolve scalable ETL/ELT pipelines for high-volume, fast-changing datasets, and partner with software engineers, analysts, product managers, and business stakeholders to translate ambiguous requirements into scalable data solutions.
Requirements
- Design, build, and evolve scalable ETL/ELT pipelines for high-volume, fast-changing datasets
- Own medium-to-large data initiatives end-to-end, from requirement shaping and technical design to production rollout and ongoing improvement
- Model reliable, analytics-ready data using proven warehouse methodologies such as Kimball, Inmon, or similar approaches
- Develop and maintain curated analytical layers, semantic models, and data marts that enable self-service and trusted decision-making
- Orchestrate robust workflows using tools such as Apache Airflow and improve reliability, observability, and maintainability of data pipelines
- Partner with software engineers, analysts, product managers, and business stakeholders to translate ambiguous requirements into scalable data solutions
- Proactively identify data quality, performance, and modeling issues and drive improvements before they become business problems
- Contribute to architecture and engineering decisions within your domain, balancing speed, quality, and long-term maintainability
- Mentor less senior data engineers through code reviews, design discussions, documentation, and day-to-day guidance
- Raise the engineering bar through testing, automation, CI/CD practices, clear documentation, and thoughtful technical standards