Job Summary:
We are seeking an experienced Big Data Test Manager to lead quality engineering and testing initiatives for enterprise-scale data platforms, Big Data applications, ETL/ELT pipelines, and cloud-based data solutions. The Test Manager will provide overall test strategy, planning, execution, governance, and delivery leadership across data engineering and analytics initiatives. The ideal candidate will combine strong technical knowledge with exceptional communication, collaboration, stakeholder management, leadership, and problem-solving skills.
Key Responsibilities
* Lead end-to-end testing activities across Big Data, data engineering, ETL/ELT, data warehouse, and cloud data platforms.
* Define and execute comprehensive test strategies, test plans, estimates, schedules, resource plans, and quality metrics.
* Lead and mentor QA teams consisting of data testers, automation engineers, and other testing resources.
* Manage testing for Databricks, Azure Data Factory (ADF), Spark/PySpark, Hadoop, Hive, Delta Lake, and enterprise data pipelines.
* Establish standards for data validation, source-to-target testing, reconciliation, data quality, and end-to-end testing.
* Oversee functional, integration, system, regression, performance, UAT, and production validation testing.
* Drive development and adoption of test automation frameworks and continuous testing practices.
* Promote BDD, Gherkin, TDD, shift-left testing, and automation practices.
* Lead defect triage, root-cause analysis, risk assessment, and resolution activities.
* Coordinate testing dependencies across development, data engineering, architecture, business, infrastructure, and release teams.
* Ensure test environments, test data, access, and infrastructure are available and ready.
* Provide clear and timely communication of testing progress, risks, issues, dependencies, quality metrics, and release readiness to project and client leadership.
* Support Agile ceremonies and contribute to sprint planning, backlog refinement, reviews, retrospectives, and release planning.
* Drive continuous improvement of QA processes, automation, tools, and testing methodologies.
Communication & Collaboration Skills — Critical
* Excellent verbal and written communication skills, with the ability to communicate effectively with both technical and non-technical audiences.
* Strong ability to translate complex technical testing and data issues into clear business-level impacts and actionable recommendations.
* Build strong working relationships with business stakeholders, product owners, developers, data engineers, architects, QA teams, project managers, and client leadership.
* Act as a strong bridge between business, technology, development, data engineering, and QA teams.
* Proactively communicate risks, dependencies, blockers, and potential impacts rather than waiting for issues to escalate.
* Facilitate effective cross-functional discussions, defect triage meetings, testing reviews, and stakeholder meetings.
* Demonstrate strong listening skills and the ability to understand different stakeholder perspectives and priorities.
* Ability to manage disagreements constructively and drive teams toward practical, fact-based resolutions.
* Build trust and maintain positive relationships across onshore and offshore/distributed teams.
* Demonstrate strong presentation skills and the ability to present testing status, quality metrics, risks, and recommendations to senior leadership.
* Take ownership and accountability for testing commitments while maintaining a collaborative team environment.
* Demonstrate strong interpersonal skills, professionalism, adaptability, and the ability to work effectively in a fast-paced enterprise environment.
Leadership & Management
* Provide technical and delivery leadership to distributed QA and testing teams.
* Plan resources, manage capacity, prioritize testing activities, and balance competing project demands.
* Mentor and develop team members while establishing consistent testing standards and best practices.
* Coordinate multiple testing workstreams and manage cross-team dependencies.
* Work closely with project and delivery leadership on planning, estimation, staffing, risks, issues, and release readiness.
* Manage vendor and partner testing activities when applicable.
* Establish a culture of quality, accountability, collaboration, continuous improvement, and proactive communication.
Technical Skills
Strong understanding of Databricks, Azure Data Factory (ADF), Apache Spark, PySpark, Hadoop, HDFS, Hive, SQL, ETL/ELT, data lakes, Delta Lake, and data warehousing. Strong experience with data validation, reconciliation, data quality, complex SQL testing, and large-volume data testing is required.
Testing & Automation Tools
Experience with Selenium, Cucumber, Gherkin, Postman, REST Assured, JMeter, PyTest, JUnit/TestNG, or equivalent frameworks. Experience with JIRA, Azure DevOps, HP ALM/Quality Center, or similar test and defect management tools is preferred.
BDD / TDD / CI-CD
Experience implementing BDD, Gherkin-based acceptance testing, TDD, unit testing, automated integration testing, regression automation, and continuous testing practices. Experience integrating automated testing with Azure DevOps, Jenkins, GitHub Actions, or similar CI/CD platforms is preferred.
Preferred / Optional Skills
Experience with AWS and AWS data services such as S3, Glue, EMR, and Lambda is preferred but not mandatory. Experience with Kafka, Control-M, Power BI, SSRS, Tableau, and healthcare or insurance data platforms is also beneficial.
