Monitor, investigate, and resolve issues across data ingestion pipelines, and go beyond firefighting to implement lasting solutions.
Act as a data expert: optimize queries, contribute to data architecture decisions, and help teams get the most out of their data.
Provide infrastructure support that improves scalability, stability, and security across internal systems.
Raise the bar for code quality through automation, unit testing, and thoughtful code reviews.
Document code, design decisions, and data sources so your work is maintainable and your teammates can build on it.
Collaborate across disciplines to untangle complex data challenges, and enjoy doing it.

5+ years of experience as a Data Engineer, with a strong background in data infrastructure.
Solid problem-solving skills and the ability to juggle multiple priorities without dropping the ball.
Experience designing and maintaining data pipelines with an eye for performance and reliability.
A proactive, ownership-driven attitude, you spot problems before they escalate.
Strong English communication skills (B2/C1). You'll work closely with cross-functional teams and need to articulate both technical and non-technical ideas clearly.
Experience supporting ML platforms or working alongside data science/ML teams.
Familiarity with cloud platforms (AWS, GCP, or Azure).
Knowledge of observability tools, logging, metrics, and tracing.
A track record of improving system reliability through automation and monitoring.

ML Data Engineer

Key skills