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NielsenIQ

Data Engineer

Posted Yesterday
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Hybrid
Chennai, Tamil Nadu, IND
Mid level
Hybrid
Chennai, Tamil Nadu, IND
Mid level
Build and manage secure, scalable Python and Snowflake data pipelines supporting analytics, reporting, machine learning, and data products. Responsibilities include ETL/ELT development, SQL optimization, cloud orchestration, CI/CD, testing, security scanning, IAM, observability, data quality, documentation, and collaboration with analytics and ML teams. The role also emphasizes responsible use of AI-assisted engineering tools such as GitHub Copilot.
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Company Description

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

Job Description

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 

What You’ll Do (Key Responsibilities) 

  • Data Pipelines & ETL/ELT  

  • Develop, schedule, and monitor ELT/ETL pipelines in Python to ingest data from APIs, files, and databases into Snowflake. 

  • Implement 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  

  • Build 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. 

  • Apply AI tools to speed up pipeline scaffolding, DAG generation, and configuration validation 

  • DevSecOps & Reliability  

  • Apply CI/CD for data code (linting, unit/data tests, IaC review gates). 

  • Embed security scanning (dependencies, IaC policies), secrets management, and least‑privilege IAM. 

  • Contribute to observability (logging, metrics, lineage, data quality checks). 

  • Use AI responsibly to assist with test generation, documentation, and failure analysis 

  • Collaboration  

  • Work with Analytics/ML teams to productize models and enable self‑service. 

  • Write clear documentation (readme, runbooks, data dictionaries). 

  • Actively learn and upskill in AI‑driven engineering practices, sharing learnings with the team 

Qualifications

 

  • 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: Strong 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 

  • Ability to critically evaluate AI‑generated code and ensure correctness, security, and performance 

  • Strong problem-solving, curiosity, and ability to learn quickly. 

 

     

    Additional Information

    Nice-to-Have 

    • Orchestration: Airflow/Prefect/ADF/Composer. 

    • IaC: Terraform/Azure Bicep/CloudFormation; policy-as-code (e.g., OPA/Conftest). 

    • Streaming: Kafka/Kinesis/PubSub; Change Data Capture. 

    • dbt (models, tests, exposures) and semantic layer concepts. 

    • Basic SCD/CDC design patterns; Dimensional modeling (Kimball). 

    • Security: OWASP, least privilege, key rotation, secret stores (AWS Secrets Manager/Azure Key Vault). 

    • Observability: OpenLineage, DataDog/CloudWatch/Log Analytics; SLA/SLO thinking. 

    • Exposure to MLOps (feature stores, model serving) is a plus 

    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://nielseniq.com/global/en/info/niqs-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

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