{"id":3135721,"url":"https://alion.io/job/nielseniq-data-engineer-5","title":"Data Engineer","company":{"id":9378,"name":"NielsenIQ","domain":"nielseniq.com","url":"https://alion.io/company/nielseniq","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":80,"open_postings":16,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":14,"computed_at":"2026-10-24T06:02:35Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":11000,"max_usd":28000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":21},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Copilot","optional":false},{"name":"dbt","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab CI","optional":false},{"name":"Great Expectations","optional":false},{"name":"IAM","optional":false},{"name":"Least Privilege","optional":false},{"name":"Prefect","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"SQLAlchemy","optional":false},{"name":"Amazon CloudWatch","optional":true},{"name":"Amazon Kinesis","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Bicep","optional":true},{"name":"CloudFormation","optional":true},{"name":"Datadog","optional":true},{"name":"Dimensional Modeling","optional":true},{"name":"Feature Store","optional":true},{"name":"OWASP","optional":true},{"name":"SLI/SLO/SLA","optional":true},{"name":"Terraform","optional":true}],"status":"closed","first_seen_at":"2026-10-23T05:22:17Z","employer_posted_date":"2026-10-23","last_verified_at":"2026-10-24T19:41:55Z","board_verified":false,"closed_at":"2026-10-24T19:41:55Z","days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"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\n 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.\nYou’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\nWhat You’ll Do (Key Responsibilities)\nData Pipelines & ETL/ELT\n\nDevelop, schedule, and monitor ELT/ETL pipelines in Python to ingest data from APIs, files, and databases into Snowflake.\n\nImplement transformations (SQL & Python) following modular, reusable patterns.\n\nLeverage AI-assisted tooling (e.g., GitHub Copilot) to accelerate development, improve readability, and reduce boilerplate-while ensuring correctness through reviews and testing\n\nSnowflake Engineering\n\nBuild tables, views, stages, and secure data shares.\n\nTune queries and warehouse configs; manage roles, RBAC, and resource usage.\n\nUse AI assistance to analyze query performance, refactor SQL, and identify optimization opportunities\n\nCloud & Orchestration\n\nUse cloud services (AWS/GCP/Azure) for storage, compute, and event triggers (e.g., S3/Blob/GCS; Lambda/Functions).\n\nOrchestrate jobs (Airflow/Cloud Composer/Prefect/Azure Data Factory) with proper alerting & SLAs.\n\nApply AI tools to speed up pipeline scaffolding, DAG generation, and configuration validation\n\nDevSecOps & Reliability\n\nApply CI/CD for data code (linting, unit/data tests, IaC review gates).\n\nEmbed security scanning (dependencies, IaC policies), secrets management, and least-privilege IAM.\n\nContribute to observability (logging, metrics, lineage, data quality checks).\n\nUse AI responsibly to assist with test generation, documentation, and failure analysis\n\nCollaboration\n\nWork with Analytics/ML teams to productize models and enable self-service.\n\nWrite clear documentation (readme, runbooks, data dictionaries).\n\nActively learn and upskill in AI-driven engineering practices, sharing learnings with the team\n\n 3-5 years of experience in data engineering, analytics engineering, or backend engineering (internships/co-ops included).\n\nProgramming: Python (pandas, SQLAlchemy/DB APIs, typing, testing with pytest).\n\nSQL & Warehousing: Strong SQL; experience with Snowflake (warehouses, stages, tasks, Snowpipe, RBAC).\n\nCloud Basics: Familiarity with one major cloud (AWS/Azure/GCP) and storage + compute + IAM fundamentals.\n\nDevSecOps Mindset: Git, CI/CD (GitHub Actions/Azure DevOps/GitLab CI), code reviews, secret handling, dependency scanning.\n\nData Quality: Exposure to unit tests, data validation (e.g., Great Expectations/dbt tests), and monitoring principles.\n\nAI-Aware Engineering:\n\nExperience or willingness to adopt GitHub Copilot or similar AI tools\n\nAbility to critically evaluate AI-generated code and ensure correctness, security, and performance\n\nStrong problem-solving, curiosity, and ability to learn quickly.\n\nNice-to-Have\nOrchestration: Airflow/Prefect/ADF/Composer.\n\nIaC: Terraform/Azure Bicep/CloudFormation; policy-as-code (e.g., OPA/Conftest).\n\nStreaming: Kafka/Kinesis/PubSub; Change Data Capture.\n\ndbt (models, tests, exposures) and semantic layer concepts.\n\nBasic SCD/CDC design patterns; Dimensional modeling (Kimball).\n\nSecurity: OWASP, least privilege, key rotation, secret stores (AWS Secrets Manager/Azure Key Vault).\n\nObservability: OpenLineage, DataDog/CloudWatch/Log Analytics; SLA/SLO thinking.\n\nExposure to MLOps (feature stores, model serving) is a plus\n\nOur Benefits\nFlexible working environment\nVolunteer time off\nLinkedIn Learning\nEmployee-Assistance-Program (EAP)\nNIQ 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/\nAbout NIQ\nNIQ 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.\nFor more information, visit NIQ.com\nWant to keep up with our latest updates?\nFollow us on: LinkedIn | Instagram | Twitter | Facebook\nOur commitment to Diversity, Equity, and Inclusion\nAt 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","description_format":"text","description_chars":6959,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":false}]},"benefits":["Continuous learning","Equity","Flexible schedule"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Market Research","Retail & Pricing Analytics"],"lifecycle":[{"event":"open","at":"2026-10-23T05:36:02Z"},{"event":"close","at":"2026-10-24T19:41:55Z"}],"visa":[],"liveness":null,"pay":null,"html_url":"https://alion.io/job/nielseniq-data-engineer-5","json_url":"https://alion.io/job/nielseniq-data-engineer-5.json","meta":{"generated_at":"2026-10-24T20:33:45Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":29980,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-25T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":9378},"rest":"https://alion.io/mcp/rest/get_company?id=9378"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fnielseniq-data-engineer-5"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fnielseniq-data-engineer-5"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fnielseniq-data-engineer-5"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/nielseniq-data-engineer-5\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fnielseniq-data-engineer-5"}]}