Quality Assurance Engineer

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Anika Systems

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤝 B2B

🏛️ Government

🤖 Artificial Intelligence

B2B • Government • Artificial Intelligence

Anika Systems is an outcome-driven technology solutions provider specializing in assisting Federal agencies in meeting their mission goals and preparing for the future. The company offers a range of services including Data and Analytics, Intelligent Automation, Application Development, IT Modernization, and Cloud Engineering. Anika Systems collaborates with Federal agencies to create long-term, innovative, and empowering solutions, focusing on delivering goals successfully on time and within budget. Their capabilities include data strategy, machine learning, cloud transformation, and more, leveraging partnerships with platforms like Microsoft Azure and Red Hat to enhance their offerings.

📋 Description

• 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. • 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. • Develop and execute test strategies for Apache Iceberg-based data lakehouse architectures. • Ensure alignment between precomputed datasets (materialized views) and underlying source data. • Implement automated validation for data quality rules, lineage, and metadata accuracy. • Collaborate with data and AI teams to test data pipelines supporting RAG, analytics, and machine learning workflows. • Document test results, defects, and quality metrics for both technical and non-technical stakeholders. • Promote adoption of AI-driven efficiencies and automation across QA and data engineering workflows.

🎯 Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field. • 5+ years of experience in QA engineering, data testing, or software development. • Strong programming skills in Python and advanced proficiency in SQL. • Experience building automated test frameworks for data platforms and ETL pipelines. • Hands-on experience with: AWS data services (S3, Glue, Redshift, Lambda, etc.) • Experience validating materialized views and performance-optimized data structures. • Familiarity with XBRL or complex financial/regulatory datasets. • Understanding of data modeling, metadata, and data governance principles. • Experience with CI/CD tools and automated testing integration. • Demonstrated proficiency with AI tools and AI-assisted development/testing workflows. • Understanding of data quality requirements for AI/ML and analytics use cases. • U.S. Citizenship required; ability to obtain and maintain a federal clearance.

🏖️ Benefits

• 100% remote work • Professional development opportunities