About The Position
Plume’s Data Services team is looking for engineers to build and operate data pipelines that power the gamut of Plume products and analytics. Due to the massive scale and performance requirements of many of our use cases, you will be solving challenging problems on a daily basis using a variety of cutting-edge technologies.
Requirements
- 5+ years of software development experience building, scaling, and supporting production data pipelines
- Hands-on expertise with AWS big data services particularly Athena for distributed querying and Lake Formation for security, cataloging, and access management
- Solid Apache Airflow experience: writing DAGs, managing task dependencies, and debugging runtime failures
- A DataOps mindset comfortable with CI/CD for pipelines, environment monitoring, IAM/permissions management, and owning what you ship
- Strong Python skills for scripting, automation, and Airflow orchestration; proficiency in Java or Scala for core pipeline development
- High proficiency in SQL across data warehousing technologies
- Deep understanding of large-scale data processing frameworks, preferably Apache Spark (Flink experience a plus)
- Solid grasp of data warehousing concepts and design patterns
- Strong analytical thinking and clear, effective communication written and verbal
Nice To Haves
- Flink experience a plus
Responsibilities
- Partner with stakeholders to define data requirements and translate them into robust pipeline designs
- Build and maintain high-quality data pipelines with strong reliability and data integrity standards
- Own data warehouse schema documentation and keep it current as systems evolve
- Write clean, well-structured code and contribute to a culture of rigorous peer review
- Continuously refactor and optimize pipelines for performance, cost efficiency, and operational simplicity
- Triage and resolve production issues related to data quality and availability
- Mentor junior engineers and new hires, helping them ramp up quickly and contribute confidently
- Uphold data governance requirements including access controls, retention policies, residency rules, and de-identification
- Contribute to the technology roadmap and drive best practice adoption across the team
- Orchestrate complex workflows in Apache Airflow writing DAGs, managing dependencies, and building in automated error handling
- Implement granular access controls and data security policies using AWS Lake Formation
- Integrate automated data quality checks into deployment pipelines so issues are caught before they reach production
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
