> Markdown version of [/jobs/ext/4462012-microsoft-fabric-technical-lead-for-data-quality-and-governance](https://www.wearedevelopers.com/jobs/ext/4462012-microsoft-fabric-technical-lead-for-data-quality-and-governance). 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).

---

# Microsoft Fabric Technical lead for data quality and governance

- **Company:** SANFORD AI TECHNOLOGIES LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $124,800 - $135,200
- **Contract:** Permanent contract
- **Skills:** Query Performance, Application Programming Interfaces (APIs), Data Analysis, Code Reuse, Code Review, Data Governance, Dimensional Modeling, Apache Hive, Intrusion Detection Systems, Python (Programming Language), Regular Expressions, Power BI, Azure DevOps Pipelines, SQL Databases, Transact-SQL, Great Expectations (Foster Youth College-readiness and Support Program), Git, Microsoft Fabric, Data Lakes, Pyspark, Collibra, Software Coding, Restful APIs, Software Version Control, Databricks
- **Published:** October 15, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=bc4d9fd371fd3df0

## About the Role

* Delta Lake or Lakehouse experience (Microsoft Fabric, Databricks, or Synapse)

 * Data quality frameworks: Great Expectations, Deequ, dbt tests, Soda, or equivalent

 * Regex for pattern validation (policy numbers, IDs, dates)

 * Column-level lineage and impact analysis

 * REST API work, ideally Purview Data Map or other catalog APIs, for bulk metadata updates

 * Reads DAX well enough to confirm a Power BI measure matches its glossary definition

Nice-to-Haves

 * Any catalog or governance tool: Purview, Collibra, Alation, Informatica, Unity Catalog

 * Azure DevOps pipelines

 * Insurance or financial services; annuities a plus

 * Experience leading offshore teams

## Description

* Design, code, and maintain data quality rules for critical data elements across policy, agent, client, marketing, and customer service domains

 * Build reusable validation notebooks in PySpark and SQL against Delta tables in Fabric lakehouses and warehouses

 * Profile new sources statistically before they are certified for reporting: distributions, cardinality, null patterns, outliers, drift

 * Build source-to-target reconciliation across raw, cleansed, and curated layers

 * Trace quality failures through pipeline code and lineage to the originating system or transform

 * Validate SCD Type 2 history: overlapping effective dates, gaps, multiple current rows, broken key chains

 * Implement and tune rules in Purview Unified Catalog data quality; extend coverage with code where native rules fall short

 * Set technical standards, rule templates, and code review criteria for offshore analysts

 * Lead definition sessions with business owners and record decisions in the business glossary

 * Report governance health and quality trends to the Data Governance Council

Must-Haves (screen on these)

 * 5+ years in data quality, data analysis, or analytics engineering with daily hands-on coding

 * Expert SQL (T-SQL or Spark SQL): window functions, CTEs, recursive queries, PIVOT/UNPIVOT, query performance on large tables

 * Python with PySpark or pandas for profiling and validation, written as reusable code, not one-off scripts

 * Has built automated data quality checks that run on a schedule or in a pipeline, with thresholds and alerting

 * Source-to-target reconciliation using counts, aggregates, and row-level hash comparisons

 * Dimensional modeling depth: grain, surrogate vs. natural keys, SCD Type 2 behavior and its effect on point-in-time queries

 * Statistical profiling: distributions, percentiles, standard deviation, and spotting anomalies or drift over time

 * Git-based version control for SQL and Python