Data Engineer
Build and optimize data pipelines for ML use cases on GCP
Design and build data pipelines and flows for machine learning use cases using Python and distributed systems like Dask or Spark. Deploy and manage these pipelines in orchestration tools such as Airflow or Dagster, ensuring reliability through data quality checks and CI/CD improvements. Optimize processing jobs for performance and cost on cloud data services, particularly within GCP environments including BigQuery, Cloud Storage, and GKE.
Why This Role?
Work on ML-focused data pipelines with direct impact on consumer intelligence products at a global leader
Key Responsibilities
- Design and build data pipelines for machine learning use cases
- Deploy and manage data flows using orchestration tools like Airflow or Dagster
- Improve and maintain CI/CD pipelines for data workflows
- Manage Python dependencies using Poetry and uv
- Deploy data scientists' scripts and models from notebooks to production
- Implement data quality checks to ensure pipeline reliability
Requirements
- 3–5 years of experience as a Data Engineer
- Strong proficiency in Python
- Experience with distributed systems for big data processing (Dask, Spark)
- Experience building ETL and reliable data pipelines
- Hands-on experience with GCP core data services (Cloud Storage, BigQuery, Cloud Build, GKE)
- Experience with orchestration tools (Airflow, Dagster, or similar)
Required Skills
Indonesia Context
- Working Hours Overlap:
- Flexible — work your own hours
View Original Description from SmartRecruiters
Original description from SmartRecruiters
Responsibilities Design and build data pipelines/flows for ML use cases Implement data versioning practices Deploy and manage flows in orchestration tools Improve and maintain CI/CD pipelines Manage Python dependencies (Poetry, uv) Deploy data scientists' scripts and models from notebooks to production Implement data quality checks to ensure pipeline reliability Optimize data processing jobs for performance and cost, particularly on distributed systems and cloud data services Qualifications 3–5 years of experience as a Data Engineer Strong proficiency in Python Experience with distributed systems for big data processing (Dask, Spark) Experience building ETL pipelines Experience building reliable, maintainable data pipelines Hands-on experience with GCP core data services (Cloud Storage, BigQuery, Cloud Build, GKE) Experience with orchestration tools (Airflow, Dagster, or similar) Comfortable working in a Linux environment with Jupyter, Python, Git, Docker, SQL, and NoSQL Strong experience with Pandas, SQL, and writing Dockerfiles Professional-level English Nice to have Experience with ML datasets Experience building data pipelines for AI models Experience with LangGraph and RAG systems 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 Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook 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
Salary Context
Similar Engineering roles on LokerDollar pay around $170k/yr (range $1.8k–1000k/yr, n=680 active listings).
Hiring at NielsenIQ
NielsenIQ has 43 other active roles on LokerDollar and has been hiring here since Apr 9, 2026 — across Engineering, Data & Analytics, Finance & Accounting.
View all NielsenIQ openings →Openness not stated by employer — check the listing
Frequently asked questions
- Is Data Engineer at NielsenIQ a remote job?
- This role is based in Remote. See the listing for remote/onsite details.
- What type of employment is Data Engineer at NielsenIQ?
- This is a full time position.
- How do I apply?
- Click the "Apply" button on this page to go to the official application at NielsenIQ.
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