Data Engineer

Job description

Job responsibilities

• 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;
• Also, you get to drive 100,000 lb excavators.

Job requirements

• 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
• Hands-on experience with Databricks and Spark
• Experience with streaming or near-real-time ingestion patterns