Business Title
Years of Experience
10+
The purpose of this role is to ensure the developed software meets the client requirements and the business’ quality standards within the project release cycle and established processes. To lead QA technical initiatives in order to optimize the test approach and tools.
1.At least 2 years in a lead role.
2.Experience with Azure cloud.
3.Testing file-based data lake solutions or Big data based solution.
4.Worked on migration or implementation of Azure Data Factory projects.
5.Strong experience in ETL/data pipeline testing, preferably with Azure Data Factory.
6.Proficiency in SQL for data validation and test automation.
7.Familiarity with Azure services: Data Lake, Synapse Analytics, Azure SQL, Key Vault, and Logic Apps.
8.Experience with test management tools (e.g., Azure DevOps, JIRA, TestRail).
9.Understanding of CI/CD pipelines and integration of QA in DevOps workflows.
10.Experience with data quality frameworks (e.g., Great Expectations, Deequ).
11.Knowledge of Python or PySpark for data testing automation.
12.Exposure to Power BI or other BI tools for test result visualization.
13.Azure Data Factory
14.Exposure to Azure Databricks
15.SQL/stored procedure on SQL Server
16.ADLS Gen2
17.Exposure to Python/ Shell script
1.Exposure to any ETL tool experience.
2.Any other Cloud experience (AWS / GCP).
3.Exposure to Spark architecture, including Spark Core, Spark SQL, DataFrame, Spark Streaming, and fault tolerance mechanisms.
4.ISTQB or equivalent QA certification.
5.Working experience on JIRA and Agile
6.Experience with testing SOAP / API projects
7.Stakeholder communication
Key responsibiltes
1.Lead the QA strategy, planning, and execution for ADF-based data pipelines and workflows.
2.Design and implement test plans, test cases, and test automation for data ingestion, transformation, and loading processes.
3.Validate data accuracy, completeness, and integrity across source systems, staging, and target data stores (e.g., Azure SQL, Synapse, Data Lake).
4.Collaborate with data engineers, architects, and business analysts to understand data flows and ensure test coverage.
5.Develop and maintain automated data validation scripts using tools like PySpark, SQL, PowerShell, or Azure Data Factory Data Flows.
6.Monitor and report on data quality metrics, defects, and test coverage.
7.Ensure compliance with data governance, security, and privacy standards.
8.Mentor junior QA team members and coordinate testing efforts across sprints.
12 PM to 9 PM and / or 2 PM to 11 PM - IST time zone
DGS India - Pune - Indiqube Orchid
Merkle
Full time
Permanent
We are dentsu. We team together to help brands predict and plan for disruptive future opportunities and create new paths to growth in the sustainable economy. We know people better than anyone else and we use those insights to connect brand, content, commerce and experience, underpinned by modern creativity. We are the network designed for what’s next.
