Data Engineer

- You will design, build, and maintain robust, scalable data pipelines and ingestion workflows across a growing Data Lake;

- Define and enforce data quality standards, SLOs, and validation frameworks to ensure accuracy and reliability of critical data assets;

- Continuously optimize existing pipelines for performance and cost efficiency as data volumes scale;

- Expand and own our monitoring and alerting coverage - surfacing data issues before they become customer-facing problems;

- Drive best practices around data modeling, partitioning, and compute resource utilization;

- 5+ years of experience in data engineering, with a strong track record in large-scale data lake or data warehouse environments

- 5+ years of experience working with SQL and distributed query engines (e.g. Spark, BigQuery, Snowflake, or similar)

- Deep proficiency with pipeline orchestration tools (e.g. Airflow, Prefect, or equivalent) and transformation frameworks (e.g. Spark)

- Experience designing and implementing data quality frameworks - validation, anomaly detection, lineage tracking

- Familiarity with observability tooling for data systems: monitoring, alerting, and incident response for data pipelines

- Experience enabling non-engineering stakeholders to self-serve on data infrastructure, whether through documentation, tooling, or hands-on enablement

- Experience with streaming or near-real-time ingestion patterns

- Familiarity with data governance and access control at scale

- Background working on customer-facing data products or external SLAs