Position: Technical Lead - QA / Data Testing - Technical Lead
Location: Remote
Experience: 12+
Looking for QA/Data testing candidate here, also looking for lead level candidate here, who can lead offshore team. Look for senior 12, 13+
Hands-on testing experience with:
Snowflake
Databricks (PySpark & SQL)
Azure Data Factory (ADF)
Candidate should be very strong in SQL(this is must), python – pytest, pandas, ,,, “Azure devops”
Role Summary
The Technical Lead is the hands-on technical authority for the offshore QA team. This role owns the technical direction for testing across Snowflake, Databricks, and Azure Data Factory, sets standards for test design and automation, and serves as the primary technical escalation point for complex data quality issues, schema changes, and root cause analysis. The Technical Lead partners closely with the Onshore Team Lead on prioritization, delivery, and stakeholder communication.
Key Responsibilities
Define the technical testing strategy across Snowflake, Databricks, and Azure Data Factory, including data quality frameworks, validation patterns, and test data management approaches.
Establish and enforce QA standards, best practices, and reusable accelerators (test harnesses, validation libraries, SQL templates) for the team.
Provide technical oversight on test design for functional and regression testing, schema evolution, source-to-target validation, reconciliation, and backfill/reprocessing verification.
Lead complex root cause analysis for data quality incidents, including impact assessment, and coordinate resolution with data engineering teams.
Own the automation roadmap; review and approve Python-based test scripts, SQL-based validations, and DevOps pipeline integrations (Azure DevOps).
Mentor the Sr. QA Engineer, Automation QA Engineer, and QA Engineers/Testers; perform code and test case reviews.
Partner with the Onshore Team Lead on sprint planning, capacity, risk identification, and stakeholder communication.
Monitor data quality KPIs, dashboards, and alerts; drive continuous improvement initiatives based on trends and incident patterns.
Support schema changes, backward compatibility analysis, and impact assessment for upstream/downstream consumers.
Required Skills & Experience
5–8 years of QA / data testing experience, with at least 2 years in a technical lead or senior IC capacity.
Strong hands-on experience testing data pipelines on Snowflake, Databricks (PySpark / SQL), and Azure Data Factory.
Advanced SQL: complex joins, window functions, reconciliation queries, and performance-aware query writing.
Proficiency in Python for test automation, including frameworks such as pytest and libraries such as pandas, Great Expectations, or equivalent.
Experience with Azure DevOps (or equivalent CI/CD) for automated test execution, pipeline integration, and reporting.
Solid understanding of data warehousing concepts, ELT/ETL patterns, schema evolution, slowly changing dimensions, and data reconciliation.
Demonstrated experience leading RCA for data incidents and communicating findings to technical and business stakeholders.
Strong written and verbal communication skills; able to work across onshore/offshore time zones.
Nice to Have
Experience with data quality tools such as Great Expectations, Soda, Monte Carlo, or Collibra DQ.
Exposure to data governance, lineage, and metadata management tooling.
Azure certifications (DP-203, AZ-400) or Snowflake / Databricks certifications.
Experience with Git-based workflows, code reviews, and trunk-based development practices.
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