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Databricks Engineer Test Data Management

  • Databricks Engineer Test Data Management job type Posted on: Nov 12, 2026
  • Databricks Engineer Test Data Management experience level Conch Technologies Inc
  • Databricks Engineer Test Data Management employment type Chicago, Illinois
  • Databricks Engineer Test Data Management employment type Remote
  • Databricks Engineer Test Data Management salary Full-time
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Job Title :

Databricks Engineer Test Data Management

Job Type :

Full-Time

Job Location :

Chicago Illinois United States

Remote :

Yes

Jobcon Logo Job Description :

Hello,
Position: DataBricks Engineer (Test Data Management)
Location: 100% Remote
Duration: 6+months
Job Description:
  • 8+ years in Data Engineering, Data Architecture, or Data Platform roles
  • 3+ years hands-on Databricks (Lakehouse, Delta Lake, Unity Catalog, PySpark)
  • Medallion Architecture implementation (Bronze/Silver/Gold)
  • Unity Catalog / data governance rollout experience
  • Enterprise data governance - Role based access control, metadata management, data classification, lineage, access control
  • Scalable ingestion, transformation, and provisioning pipelines
  • Azure (ADF, DevOps, Synapse) and/or AWS (S3, Lambda, Glue, Redshift, MWAA)
  • Python and PySpark development
Highly Desired:
  • Test Data Management (data masking, de-identification, synthetic data generation)
  • AI-powered data discovery and classification
  • Generative AI / Databricks Mosaic AI
  • Data observability and monitoring frameworks
  • Cross-team framework rollout and enablement
Nice to Have:
  • CI/CD and IaC (Terraform, Azure DevOps, GitHub Actions)
  • Regulatory compliance (PII, GDPR, CCPA, HIPAA)
Key Responsibilities:
  • Roll out TDM framework across projects on Databricks
  • Establish governance controls for sensitive data in lower environments
  • Build scalable pipelines for test data generation, masking, and refresh
  • Implement metadata management and lineage capabilities
  • Design synthetic data strategies for non-production environments
  • Enable self-service access to compliant test datasets
  • Develop reusable, automated data provisioning and lifecycle frameworks
  • Partner with QA, application teams, data governance, and security
--

Jobcon Logo Position Details

Posted:

Nov 12, 2026

Reference Number:

15341-25909

Employment:

Full-time

City:

Chicago

Job Origin:

CIEPAL_ORGANIC_FEED

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Hello,
Position: DataBricks Engineer (Test Data Management)
Location: 100% Remote
Duration: 6+months
Job Description:
  • 8+ years in Data Engineering, Data Architecture, or Data Platform roles
  • 3+ years hands-on Databricks (Lakehouse, Delta Lake, Unity Catalog, PySpark)
  • Medallion Architecture implementation (Bronze/Silver/Gold)
  • Unity Catalog / data governance rollout experience
  • Enterprise data governance - Role based access control, metadata management, data classification, lineage, access control
  • Scalable ingestion, transformation, and provisioning pipelines
  • Azure (ADF, DevOps, Synapse) and/or AWS (S3, Lambda, Glue, Redshift, MWAA)
  • Python and PySpark development
Highly Desired:
  • Test Data Management (data masking, de-identification, synthetic data generation)
  • AI-powered data discovery and classification
  • Generative AI / Databricks Mosaic AI
  • Data observability and monitoring frameworks
  • Cross-team framework rollout and enablement
Nice to Have:
  • CI/CD and IaC (Terraform, Azure DevOps, GitHub Actions)
  • Regulatory compliance (PII, GDPR, CCPA, HIPAA)
Key Responsibilities:
  • Roll out TDM framework across projects on Databricks
  • Establish governance controls for sensitive data in lower environments
  • Build scalable pipelines for test data generation, masking, and refresh
  • Implement metadata management and lineage capabilities
  • Design synthetic data strategies for non-production environments
  • Enable self-service access to compliant test datasets
  • Develop reusable, automated data provisioning and lifecycle frameworks
  • Partner with QA, application teams, data governance, and security
--
Thanks &

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