QA Lead: Data Pipeline Quality & AI-Driven Validation

Jobtailor; Austin (TX); On-site; USD 110,000 - 160,000; Full time

Job summary

Jobtailor is seeking a Senior QA Engineer focused on data quality for wealth management data pipelines in Austin. You will own the end-to-end QA strategy, design scalable test frameworks, and collaborate with data engineers to ensure data accuracy across ingestion, transformation, and delivery layers in Azure and Databricks.

The role requires 5–8 years in data quality or QA engineering with SQL and Python experience, plus hands-on validation of wealth management datasets.

Qualifications

• 5–8 years of experience in data quality, QA engineering, or data testing in wealth management contexts.
• Hands-on experience validating wealth management datasets including positions, transactions, accounts, clients, advisors, and security master data.
• Experience designing and executing reconciliation QA processes across custodians, platforms, or internal financial systems.
• Proficiency with SQL and Python for building automated data validation and testing workflows.
• Experience working with Microsoft Azure cloud environments (Azure Data Factory, Azure Data Lake, or equivalent).
• Demonstrated use of AI tools in day-to-day QA work to improve coverage and efficiency.
• Strong documentation skills for test plans and runbooks, plus root cause analyses.

Responsibilities

• Own and evolve the end-to-end QA strategy for data pipelines, ETL/ELT workflows, and financial data integrations.
• Design and implement scalable test frameworks covering data validation, schema integrity, transformation accuracy, and business rule compliance.
• Define QA standards, best practices, and documentation requirements for the data engineering team.
• Lead test planning, test case design, and execution across new pipeline builds and platform changes.
• Validate the accuracy and completeness of wealth management datasets including positions, transactions, accounts, clients, advisors, and security master data.
• Design regression test suites to prevent data quality regressions during pipeline changes.
• Collaborate with data engineers to shift quality left in the build cycle and embed QA checkpoints earlier.

Skills

SQL

Python

Azure

Databricks

Data quality

QA testing

AI tools

Documentation

Tools

Azure Data Factory

Azure Data Lake

Databricks

Job description

Jobtailor is seeking a Senior QA Engineer focused on data quality for wealth management data pipelines in Austin. You will own the end-to-end QA strategy, design scalable test frameworks, and collaborate with data engineers to ensure data accuracy across ingestion, transformation, and delivery layers in Azure and Databricks.

The role requires 5–8 years in data quality or QA engineering with SQL and Python experience, plus hands-on validation of wealth management datasets.