Mid-Level Data Processing Engineer

Software Engineer

Job Description

• We are looking for a Mid Data Processing Engineer to own and execute UAT data processing activities across dimensional and fact‑based data pipelines. This role focuses heavily on UAT planning, job execution, data validation, issue management, and coverage improvement, working closely with development and reporting teams. 

• You will act as the bridge between development, data platform, and reporting, ensuring that changes delivered by the dev team are thoroughly validated, defects are documented and resolved, and UAT confidence is high before production releases. The role also encourages AI‑assisted workflows to improve speed, accuracy, and test coverage. 

Key Responsibilities 

UAT Planning & Execution 

• Plan and manage UAT execution cycles for data processing pipelines 
• Understand release content and UAT scope for each sprint or deployment 
• Coordinate with Dev, QA, and Reporting teams to align execution timelines 
• Track UAT readiness, dependencies, and execution status 

Data Processing & Job Execution 

• Understand changes delivered by the development team across Multiple ELT/ETL data pipelines 
• Execute batch and incremental data processing jobs in UAT 
• Monitor executions, identify failures, and capture logs and evidence 
• Validate reruns and ensure consistency across execution cycles 

 

Issue Management & Defect Handling 

• Record execution failures and anomalies with clear root cause details 
• Raise bugs in tracking tools with proper reproduction steps, impact analysis, and data evidence 
• Independently analyze and resolve recurring or known issues where possible 
• Collaborate with dev teams on complex issues and verify fixes in UAT 

 

Data Validation & Reporting Validation 

• Perform end‑to‑end functional validation at:  
• Table level  
• Report / dashboard level 
• Validate transformations, aggregations, filters, treatments, and business rules 
• Ensure data consistency between source, warehouse, and reports 
• Obtain functional sign‑off from business or reporting stakeholders 

Test Coverage & Continuous Improvement 

• Identify gaps in UAT coverage and improve validation scenarios 
• Build repeatable UAT test cases and datasets 
• Promote automation of regression and functional validations 
• Improve execution reliability, runtime efficiency, and data confidence 

AI‑Assisted Productivity 

• Use AI tools (e.g., GitHub Copilot, SQL/Python assistants, documentation AI) to:  
• Analyze job failures and logs faster 
• Accelerate root cause analysis 
• Generate validation queries and test cases 
• Improve documentation and execution checklists 
• Prepare test beds 
• Apply AI responsibly by validating outputs before execution or sign‑off 

Data Stand‑up & Collaboration 

• Participate in data stand‑up activities, sharing:  
• Execution status 
• Risks and blockers 
• Defects and resolutions 
• Provide clear visibility into UAT progress and data readiness 
• Collaborate closely with:  
• Data Engineers 
• Reporting / BI teams 
• QA and Business stakeholders 

Qualifications

• 3–5 years of experience in data processing, UAT validation, data engineering, or analytics operations 
• Strong understanding of:  
• Data warehousing concepts (Dimensions, Facts) 
• Batch and incremental data processing 
• Strong SQL skills for data validation and defect analysis 
• Experience executing and validating jobs in UAT environments 
• Working knowledge of:  
• Defect management and tracking tools (Jira or similar) 
• Data quality and reconciliation techniques 
• Ability to independently troubleshoot and resolve recurring issues 
• Exposure to test automation frameworks 
• Strong communication and documentation skills 

Nice‑to‑Have Skills 

• Exposure to:  
• Snowflake or other cloud data warehouses 
• Python for basic validation or automation scripts 
• Familiarity with orchestration tools (Airflow, ADF, Control‑M, etc.) 
• Experience with data validation frameworks 
• Exposure to AI tools for analytics, development, or testing support 
• Understanding of reporting tools (Power BI, Tableau, Looker, etc.) 

Additional Information

Our Benefits

• Flexible working environment
• Volunteer time off
• LinkedIn Learning
• Employee-Assistance-Program (EAP)

NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://www.nielseniq.com/global/en/ai-safety-policies.

About NIQ

NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population.

For more information, visit NIQ.com

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Our commitment to Diversity, Equity, and Inclusion

At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence.  All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the https://nielseniq.com/global/en/news-center/diversity-inclusion

Experience Level

Mid Level