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Metro role, mid-level experience band, and recognizable global firm increase applicant competition.
Skills in data testing and automation are transferable across industries but require domain data expertise.
Explicit 4-7 years plus 2+ years data-platform focus and mandatory automation skills.
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Design, develop, and maintain automated test frameworks for enterprise data platforms, including data pipelines, APIs, and data-centric applications.
Collaborate with cross-functional teams in Agile environments to define and execute data validation test strategies covering ETL/ELT workflows, source-to-target mappings, and data quality rules.
Analyze test results, identify data defects, and drive continuous improvement in data testing processes and automation tools while reporting quality trends to stakeholders.
4-7 years of experience in software/data testing, including at least 2 years focused on enterprise data platforms, data warehouses/lakehouses, or ETL/ELT pipelines.
Strong programming and scripting skills in Python and SQL; experience with test automation frameworks like PyTest, Behave, Robot Framework or Selenium.
Experience with API/service testing tools (Postman, RestAssured, Karate), CI/CD pipelines, and test management tools (JIRA, Zephyr, TestRail).
Bachelor's degree in Computer Science, IT, Data Engineering, Analytics, or a related field.
Experienced in working with large-scale enterprise data platforms and data pipelines in an Agile delivery environment with emphasis on quality engineering and automated testing.
Able to independently design and drive data test automation, prioritize tests based on business risk and data criticality, and communicate effectively with technical and non-technical stakeholders.
Comfortable handling complex data quality issues, performing root cause analysis, and improving test processes leveraging modern data and automation technologies.