NielsenIQ: Data Engineer — Chennai, TN, India

About NielsenIQ

NielsenIQ, also known as NIQ, works in consumer intelligence and retail measurement. Its employer material describes using market information, consumer insights and analytics to help businesses understand buying behaviour. Its data operations address the accuracy and completeness of information behind client reports, while analytical services interpret that information. The business connects details about products and retail activity with broader views of markets, giving organisations evidence for understanding demand and making commercial decisions.

The position and its setting

NielsenIQ lists Data Engineer in Chennai, TN, India, under reference R26_0025230|IN. The details below separate the work described by the employer from essential conditions, preferred experience and practical preparation advice.

• Employment type: Full-time
• Employer listing date: 23 October 2026
• Brands: NielsenIQ
• Job Family: Software Engineering

Responsibilities and work described

• We’re looking for a Mid Data Engineer who’s eager to build reliable, secure, and scalable data pipelines while actively adopting AI‑assisted engineering practices
• You’ll work with Python, Snowflake, and cloud‑native services to support analytics, reporting, ML workflows, and data‑driven products
• You’ll operate with a DevSecOps mindset, treating security, testing, automation, and AI‑enabled productivity as first‑class citizens
• This role expects continuous learning and thoughtful use of tools like GitHub Copilot to improve quality, speed, and maintainability—not to replace engineering judgment
• Data Pipelines & ETL/ELT
• Develop, schedule, and monitor ELT/ETL pipelines in Python to ingest data from APIs, files, and databases into Snowflake
• Implementation: transformations (SQL & Python) following modular, reusable patterns
• Leverage AI-assisted tooling (e.g., GitHub Copilot) to accelerate development, improve readability, and reduce boilerplate—while ensuring correctness through reviews and testing
• Snowflake Engineering
• Building: tables, views, stages, and secure data shares
• Tune queries and warehouse configs; manage roles, RBAC, and resource usage
• Use AI assistance to analyze query performance, refactor SQL, and identify optimization opportunities
• Cloud & Orchestration
• Use cloud services (AWS/GCP/Azure) for storage, compute, and event triggers (e.g., S3/Blob/GCS
• Lambda/Functions)
• Orchestrate jobs (Airflow/Cloud Composer/Prefect/Azure Data Factory) with proper alerting & SLAs

Essential requirements and candidate background

• 3–5 years of experience in data engineering, analytics engineering, or backend engineering (internships/co-ops included)
• Programming: Python (pandas, SQLAlchemy/DB APIs, typing, testing with pytest)
• SQL & Warehousing: SQL; experience with Snowflake (warehouses, stages, tasks, Snowpipe, RBAC)
• Cloud Basics: Familiarity with one major cloud (AWS/Azure/GCP) and storage + compute + IAM fundamentals
• DevSecOps Mindset: Git, CI/CD (GitHub Actions/Azure DevOps/GitLab CI), code reviews, secret handling, dependency scanning
• Data Quality: Exposure to unit tests, data validation (e.g., Great Expectations/dbt tests), and monitoring principles
• AI‑Aware Engineering:
• Experience or willingness to adopt GitHub Copilot or similar AI tools
• Critically evaluate AI‑generated code and ensure correctness, security, and performance
• Problem-solving, curiosity, and ability to learn quickly

Location, schedule and contract conditions

• Work arrangement: On-site
• Advertised location: Chennai, TN, India

Benefits mentioned by the employer

• 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://nielseniq.com/global/en/info/niqs-ai-safety-policies/

Pay and application dates

A verified salary figure is not established in this article. An online estimate for another Data Engineer vacancy is not an offer for reference R26_0025230|IN; use the employer’s own pay disclosure and recruitment communication.

A closing date is not confirmed in this article. Check the current employer page before submitting: an undated posting can change or be withdrawn.

How to apply to NielsenIQ

Applications follow the official employer page linked below.

Open the official NielsenIQ posting below and match the title and reference R26_0025230|IN.

Compare your qualifications and experience with the essential conditions for the Chennai, TN, India position, then read the preferred criteria separately.

Prepare an accurate CV and the supporting items requested in that employer’s application. Provide only information and documents you are authorised to share.

Use the employer’s application option, complete the required fields and review the submission. Retain the acknowledgement when one is provided. Job Alerts World does not receive the application.

Practical preparation: Python

Python work is easier to assess through a concrete example than a list of libraries. Explain the problem, the input data, the parts you implemented and how you checked the output. Include a repository or a short technical note when you can share it.

Relevant skills

• Python
• SQL
• CI/CD
• AWS
• GCP
• Azure
• APIs
• AI/ML
• Google Cloud
• AI
• warehouse operations
• Git