Quality Assurance Engineer

Anika Systems is seeking a highly technical Quality Assurance Engineer with strong development, SQL, and Python expertise to support enterprise data platforms for federal clients. This is not a traditional manual QA role and this position requires a developer mindset, focused on automation, data validation, and platform reliability across modern cloud-based architectures.

The ideal candidate will design and implement automated testing frameworks for ETL pipelines, Apache Iceberg data architectures, XBRL datasets, and performance-optimized structures such as materialized views—ensuring data accuracy, integrity, and trust across the enterprise. This role also requires proficiency in AI tools and AI-driven workflows, leveraging automation and intelligent testing techniques to improve quality and delivery speed.

This opportunity is 100% remote.

Key Responsibilities

Test Automation & QA Engineering

* Design, develop, and maintain automated QA frameworks for data pipelines, APIs, and analytics platforms using Python and SQL. * Build reusable testing utilities for data validation, regression testing, and pipeline certification. * Integrate automated tests into CI/CD pipelines to support continuous testing and deployment. * Develop unit, integration, and end-to-end test cases for complex data workflows. * Leverage AI-assisted testing tools to generate test cases, identify edge cases, and improve test coverage.

Data Validation & ETL Testing

* Validate ETL/ELT pipelines to ensure accurate ingestion, transformation, and delivery of data. * Create automated checks for data completeness, consistency, accuracy, and timeliness. * Test ingestion and transformation of complex datasets, including XBRL financial data. * Implement reconciliation and audit mechanisms across source-to-target mappings. * Apply AI-driven anomaly detection to identify data quality issues and pipeline failures.

Iceberg & Materialized View Testing

* Develop a...