Summary of Duties & Responsibilities
The client is seeking a highly driven and technically skilled Data Quality Engineer to join their Quality Assurance AI & Analytics team. In this role, you will lead efforts to validate the integrity, accuracy, and performance of data pipelines, machine learning models, and analytics platforms. Your work will support our client's AI and Analytics data initiatives, ensuring their products meet the highest standards of quality, and reliability contributing directly to client success.
Technical:
o Advanced skills in Data Quality Engineering
o Design and implement automated testing frameworks for big data and analytics infrastructure on Microsoft Azure
o Validate APIs, data pipelines, cloud data warehouses, business intelligence platforms, and machine learning outputs
o Develop automated validation for data quality, schema, lineage, model performance, and business rule accuracy
o Establish and maintain data quality metrics, including anomaly detection and validation against training/test datasets
o Contribute to data governance, metadata management, and lineage tracking across analytical environments
Methodology:
o Apply statistical and analytical techniques to validate ML/AI model predictions and business logic
o Integrate automated tests into Agile workflows and CI/CD pipelines
o Collaborate with data scientists, ML engineers, and product teams to define quality requirements and acceptance criteria
o Promote best practices including version control, peer reviews, and reproducibility standards
o Assist with system, regression, and exploratory testing across data and AI products
Team Support /Leadership:
o Commitment to collaboration and innovation
o Test planning and execution throughout the product lifecycle, with a focus on data integrity and model reliability
o Serve as a key quality voice in cross-functional teams, aligning data quality goals with business and engineering outcomes
o Foster a culture of excellence, transparency, and continuous improvement
o Support knowledge sharing in test strategy, data validation techniques, and automation practices
o Perform related duties as required
Skills & Competencies
Abilities:
o Strong analytical and problem-solving mindset with attention to detail
o Excellent communicator who can collaborate across technical and non-technical stakeholders
o Highly adaptable and capable of managing shifting priorities in a data-driven product environment
o Self-starter who proactively identifies quality gaps and implements solutions
o Comfortable operating independently while keeping stakeholders aligned
Technical Skills:
o QA proficiency in Azure Data services (Data Factory, Fabric, Data Lake Gen2, Azure Synapse, etc.)
o Advanced SQL skills and experience with complex queries and stored procedures
o Experience testing data ingestion pipelines, real-time processing, and change data capture
o Proficient in validating Azure APIs and security mechanisms (RBAC, RLS, CLS, Azure AD Auth)
o Proven ability to validate Power BI Embedded dashboards and underlying datasets
o Skilled in test automation using Python, JavaScript, and/or C#
o Familiarity with ML/AI workflows and model validation frameworks
Education or Prior Work Experience
o Bachelors or Masters degree in Computer Science, Data Analytics, Statistics, or related field
o 6–10 years of experience in data quality assurance, with strong exposure to enterprise data platforms and AI/analytics ecosystems
o ISTQB Advanced Level and/or other relevant advanced certifications – Preferred
Veeva Systems
Datacom
Master Works
Affinity
Catalist
Inclusion Cloud
Inclusion Cloud
Inclusion Cloud