Remote Data Quality Engineer - Databricks, dbt & CI/CD

Cognizant; Hartford (CT); Remote; USD 70,000 - 117,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

Paid holidays plus Paid Time Off

401(k) plan and contributions

Long-term/Short-term Disability

Paid Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant Technology Solutions Corporation is seeking a Data Quality Engineer to design and automate data quality testing across enterprise data platforms using dbt, Python, and Databricks.

You will integrate quality checks into CI/CD pipelines with Azure DevOps, monitor key metrics, and collaborate with data engineers, analysts, and stakeholders to ensure data accuracy and reliability. This role supports a flexible, remote-friendly working model within the United States.

Qualifications

• 5+ years in QA, data testing, or data engineering roles with a focus on data validation.
• Hands-on experience with dbt (Core or Cloud): tests, macros, models, documentation.
• Strong Python skills (pandas, PySpark, pytest) for test automation.
• Practical experience with Databricks: notebooks, jobs, Delta tables, Unity Catalog.
• Experience building and maintaining Azure Pipelines (Azure DevOps) for CI/CD.
• Solid understanding of data quality concepts, dimensions, and frameworks.
• Experience with Git and version-controlled development workflows.
• Experience in using GitHub copilot

Responsibilities

• Design, build, and maintain automated data quality tests in dbt.
• Develop Python-based validation frameworks and scripts for data reconciliation, schema drift detection, and regression testing.
• Validate data pipelines and transformations in Databricks (PySpark/SQL, Delta Lake), covering source-to-target mapping, row counts, aggregations, and business rules.
• Integrate data quality gates into Azure Pipelines, so builds and releases are blocked when tests fail.
• Define, monitor, and report on data quality metrics (completeness, accuracy, consistency, timeliness, uniqueness), and set up alerting for anomalies.
• Triage and root-cause data defects with data engineers, analysts, and product owners, and track them through to resolution.
• Write and maintain test plans, test cases, and data quality documentation.
• Contribute to data governance and quality standards, including data contracts and lineage awareness.

Skills

Data validation

dbt tests

Python (pandas, PySpark, pytest)

Databricks

Azure DevOps / Azure Pipelines

Git

GitHub Copilot

Data quality concepts

CI/CD

Tools

Databricks

Azure DevOps

Git

Job description

Cognizant Technology Solutions Corporation is seeking a Data Quality Engineer to design and automate data quality testing across enterprise data platforms using dbt, Python, and Databricks.

You will integrate quality checks into CI/CD pipelines with Azure DevOps, monitor key metrics, and collaborate with data engineers, analysts, and stakeholders to ensure data accuracy and reliability. This role supports a flexible, remote-friendly working model within the United States.