> Markdown version of [/jobs/ext/2170118-data-cataloging-engineer](https://www.wearedevelopers.com/jobs/ext/2170118-data-cataloging-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Cataloging Engineer - **Company:** Guidehouse Inc. - **Location:** Washington, DC, United States - **Salary:** $74,000.0 - $124,000.0 - **Contract:** Permanent contract - **Skills:** Business Analytics Applications, Information Engineering, Data Governance, Data Infrastructure, Digital Assets, Meta-Data Management, Management of Software Versions, Data Ingestion, Apache Spark, SC Clearance, Data Lakes, Data Lineage, Data Management, Databricks - **Published:** August 21, 2026 - **Apply:** https://www.dcjobsite.com/job.asp?id=3361190422&tx=JT9486TYT&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * Active Secret clearance. * Experience supporting or working within federal government data environments. * Hands-on experience with Databricks, including Delta Lake, metadata management, and data ingestion workflows. * Understanding of enterprise data governance practices including lineage, cataloging, quality, and stewardship. * Ability to document datasets, schemas, transformations, and lineage in a structured, repeatable manner. * Strong collaboration skills to work with both technical and mission stakeholders. What Would Be Nice To Have : * Experience working within Advana or similar large-scale government analytics platforms. * Familiarity with Apache Spark, Unity Catalog, or other metadata-centric technologies in Databricks. * Knowledge of data governance frameworks such as DAMA or DoD data management policies. * Experience supporting federal data engineering or data governance workstreams tied to RFP submissions. ## Description * Build, maintain, and enhance enterprise metadata catalogs to ensure datasets are fully documented, traceable, and discoverable for mission stakeholders. * Implement data governance and cataloging standards aligned with Advana's architecture. * Operate within Databricks-based environments to capture, structure, and manage metadata for diverse data assets. * Collaborate with data engineers, platform teams, and mission analysts to ensure catalog completeness, quality, and alignment with government data governance practices. * Support ingestion workflows by tagging, classifying, and documenting datasets as they enter the ecosystem. * Monitor metadata accuracy, resolve catalog inconsistencies, and update documentation as datasets evolve. * Provide support for auditability, data lineage, schema versioning, and compliance-related metadata requirements. * Work on-site at government facilities in Washington, DC or Northern Virginia, or remotely depending on project needs. ## Related Videos - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Parquet, Delta, Iceberg & Ducklake - An introduction for developers](https://www.wearedevelopers.com/videos/100075-parquet-delta-iceberg-ducklake-an-introduction-for-developers) - [The Data Mesh as the end of the Datalake as we know it](https://www.wearedevelopers.com/videos/156-the-data-mesh-as-the-end-of-the-datalake-as-we-know-it) ## Related Articles - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j)