Lead QA Automation Engineer (Data Platforms & Databricks)

Project Description:

We are looking for a Technical Lead QA Engineer to play a pivotal role in ensuring the quality and reliability of our data platforms. You will be responsible for developing and maintaining test automation frameworks for our data pipelines, ETL processes, and backend systems. This role offers the opportunity to work on cutting-edge technologies in a highly dynamic and collaborative environment. As a key player in test automation, you will drive quality improvement initiatives, work closely with development teams, and contribute to a shift-left approach in our data operations. You'll be at the forefront of ensuring that our data infrastructure supports global investment strategy and mission.

Responsibilities:

-Design and maintain automated test frameworks (unit, integration, end-to-end),

-Driving Change and Stakeholder Engagement: Lead efforts to introduce and promote the test automation framework across teams. Drive buy-in from stakeholders and developers by demonstrating the framework's value, providing clear communication, and ensuring alignment with team goals. Help stakeholders and developers embrace automation as an integral part of the software development lifecycle,

• Automate data quality checks for platforms like Data Warehouses (DWH), Data lake, and BigData environments.

• Distribute Across Projects: Design the test tools as an individual package that can be reused in various projects, allowing multiple teams to benefit from a shared test automation solution.

-Automate API and backend testing (REST/gRPC),

-Run performance, scalability, and fault-tolerance tests,

-Integrate tests into CI/CD pipelines,

-Collaborate closely with platform, infra, and ML engineers

Mandatory Skills Description:

Minimum 8 years in QA Automation

Strong, practical experience with Python (3+ years):

• Ability to write clean, maintainable automation code

• Ability to manage and extend automation frameworks

• Not just scripting — actual engineering level proficiency

Strong, proven experience with Pytest (2+ years):

• Fixtures, parametrization, markers

• Test suite structuring

• Framework development & maintenance

Hands on experience with Git (daily usage):

• Branching strategies, PR workflows, code reviews

Hands on experience with Azure DevOps:

• Pipelines, repos, boards, test plans

Backend & API testing expertise:

• REST services, authentication, data validation

• Ability to design and automate API tests

Strong SQL and Python for test automation:

• Writing complex queries

• Data validation across ETL pipelines

Experience with Databricks (2+ years):

• Not just reading notebooks — actual testing experience

Experience with test automation tools:

• Building, maintaining, and scaling frameworks

Understanding of CI/CD processes:

• Ability to integrate tests into pipelines

Familiarity with data warehouses & ETL testing

Ability to own architecture & drive quality strategy

Experience collaborating with developers

Able to influence, challenge, and guide engineering teams

QA leadership experience

Leading initiatives, mentoring, driving standards

Fast learner, adaptable to new tools & technologies

Nice-to-Have Skills Description:

Experience in the BSFI domain

Understanding of the Investment Data Domain

Familiarity with ServiceNow

Familiarity with Dynatrace or Datadog

PySpark experience

ISTQB or equivalent certification

Languages:

English: C1 Advanced