Data Governance Engineer

What you'll do

• Design governance agents for petabyte-scale data pipelines and build integrations for policy enforcement, PII detection, and data quality validation.
• Develop intelligent monitoring, compliance reporting, and automated remediation with engineering and product partners.
• Create reusable agent workflows and contribute to reliable, scalable distributed agent systems; use AI coding agents with validation for correctness, privacy, and cost.

What they ask for

• B.S. in Computer Science or related field and 5+ years of software development experience, including exposure to ML/AI applications.
• Production experience in Python, Java, Rust, or similar languages, with familiarity in data processing and API development.
• Understanding of distributed systems and cloud platforms, including CAP theorem tradeoffs and basic ML model deployment.
• Experience with Docker, Kubernetes, infrastructure as code, CI/CD, DevOps, automated testing, and deployment workflows.

Nice to have

• Expertise in data analytics and governance platforms such as Datahub, Apache Spark, Flink, Hive, Hadoop/HDFS, and Iceberg Rest Catalog.
• Experience with multi-agent AI systems, MCP servers and APIs, MLOps, observability, and modern data platforms.

Pay

$150,400 and $277,600 (USD, base salary)

Tools

Kafka, Spark, Hadoop, Python, Java, Rust, Docker, Kubernetes

AI focus

Design autonomous governance agents and multi-agent workflows for policy enforcement, PII detection, data quality, monitoring, and remediation; use AI coding agents to accelerate implementation, testing, and debugging.