Data Engineer - Developer Platform

Design, build, and maintain robust pipelines feeding both DWH and production processesOwn pipeline orchestration in Apache Airflow end to end, including DAG design, monitoring, alerting, and production reliabilityDesign the data models behind our core domains and the contracts that downstream consumers depend onPartner with business analysts, PMs, and business stakeholders to translate product and business questions into stable, qualified, and well-modeled dataWork with a variety of data sources including product events, application data, APIs, operational databases, logs, and third-party systemsDebug and solve data quality, pipeline, performance, and reliability issuesUse and create AI agents and LLM-based tooling to improve development, testing, documentation, and root cause analysisBe part of the team and adopt effective ways of using AI tools in the engineering workflow.Requirements: 3+ years in data engineering or a similar data-focused engineering roleStrong hands-on Python and SQL skills, with the ability to write clean, performant, and maintainable codeProven track record of building and running code in large scale production environmentsDeep, hands-on Apache Airflow experience, including ownership of production DAGs at scaleDeep data modeling expertise and the ability to design clean, scalable data assets that hold up as the business changesStrong business and product orientation. You care about what the metric means, not just whether the job succeededExperience working with PMs, analysts, and business stakeholders to understand requirements and build the right data solutionsPractical experience using AI coding agents and LLM-based tools as part of your daily engineering workflowExperience working with large and varied data sources including product events, application data, APIs, operational databases, logs, and third-party systemsStrong debugging and problem-solving skills around data quality, pipeline failures, performance, and reliabilityNice to haveExperience running data workloads in containerized or Kubernetes-based environmentsExperience with large-scale or distributed processing using Spark / PySparkExperience with query engines such as TrinoExperience with CI/CD and software engineering best practicesExperience building internal tooling or agents on top of LLMs.This position is open to all candidates.