Kantar - Manager - Data Quality

4 days ago


Mumbai, India Kantar Full time

About the Role :


We are seeking a technically strong Manager - Data Quality to drive enterprise-grade data quality governance and automation strategies across our global data platforms. This role will directly contribute to the integrity, completeness, consistency, and accuracy of consumer intelligence datasets by leading efforts to design, build, and monitor robust data quality frameworks in a cloud-native ecosystem on Azure, including AKS (Azure Kubernetes Service), DataBricks, Data Factory, and Purview.


You will work at the intersection of Data Engineering, DevOps, and Data Governance, leading a team of data professionals to build and scale automated data quality checks, pipelines, and observability across distributed systems.


Key Responsibilities :


- Architect and implement scalable data quality frameworks using Python/Scala/Spark integrated with Azure Data Services (ADF, Synapse, DataBricks).


- Lead the deployment and orchestration of containerized data quality services on Azure Kubernetes Service (AKS).


- Develop and manage data observability pipelines, anomaly detection mechanisms, and data profiling systems across batch and streaming data.


- Integrate enterprise metadata and quality rules into Azure Purview for end-to-end data lineage and governance.


- Work closely with data engineering, product, and analytics teams to define data quality SLAs and KPIs, and ensure compliance.


- Automate unit, regression, and integration testing of data pipelines using tools such as Great Expectations, dbt, or custom frameworks.


- Implement CI/CD pipelines for data quality modules with GitHub Actions, Azure DevOps, or Jenkins.


- Drive root cause analysis (RCA) for data issues and proactively eliminate recurring quality failures.


- Manage and mentor a team of Data Quality Engineers and Analysts; set vision, review architecture, and enforce engineering best practices.


Required Technical Skills :


- 4 - 8 years of experience in data engineering / data quality roles in cloud-native, enterprise environments.


- Strong expertise in Azure ecosystem, especially :

  • AKS (Azure Kubernetes Service)
  • Azure Data Factory (ADF)
  • Azure Data Lake Storage (Gen2)
  • Azure Databricks / Apache Spark
  • Azure Purview / Unity Catalog

- Proficient in scripting and programming with Python, PySpark, SQL, and optionally Scala.


- Hands-on experience with containerization and orchestration (Docker, Helm, Kubernetes).


- Experience with monitoring tools like Prometheus, Grafana, and integration with data observability platforms (e.g., Monte Carlo, Databand).


- Familiarity with data testing and validation tools: Great Expectations, Deequ, dbt tests, or similar.


- Solid understanding of data governance, MDM, lineage, and cataloging concepts.


- Comfortable working in Agile/Scrum methodologies and distributed global teams.

(ref:hirist.tech)

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