Job Description
This role is a highly technical Data Quality Engineer supporting enterprise data pipelines in Azure/Databricks. Reporting into a senior lead, this individual will act as a junior counterpart and key liaison between data lake and data insights teams. The ideal candidate is a strong hands-on data engineer with deep experience in Azure, PySpark, and pipeline validation. Other key responsibilities include:
• Validating and monitoring enterprise data pipelines across Azure (ADF, Databricks, ADLS)
• Own end-to-end data validation, testing, and automation across ingestion, transformation, and consumption layers
• Build and maintain data quality frameworks, SLAs, and monitoring dashboards
• Partner across data lake & insights teams to ensure data accuracy, reliability, and pipeline health
• Drive automation initiatives (Python/PySpark) to scale validation and reduce manual effort
Develop Power BI dashboards for operational data health tracking
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Required Skills & Experience
• 9–11+ years experience in data engineering / data quality / data architecture
• Strong hands-on with Azure Data Factory + Databricks (PySpark)
• Experience with large-scale data validation using SQL & PySpark
• Proven experience building data quality frameworks, rules, and validation logic
• Strong understanding of data governance, lineage, and metadata
• Experience integrating with enterprise systems (ERP, CRM, MDM, etc.)
Ability to work hands-on in code (Python/PySpark) and troubleshoot real-time data issues
Nice to Have Skills & Experience
• Exposure to monitoring tools (Monte Carlo, Datadog)
• Experience building CI/CD data testing pipelines (Azure DevOps / GitHub Actions)
• Experience within supply chain or large enterprise data environments
Exposure to AI / automation for data validation
Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.