Data Engineer (MId)

We are looking for a motivated Mid-level Data Engineer to join our data team. You will be responsible for building, maintaining, and evolving data pipelines (ETL / ELT / data-processing / model-training pipelines) to support analytics, reporting, and machine learning workflows. You will work with large, complex datasets and ensure our data infrastructure is scalable, reliable, and aligned with best practices.

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  Design, implement, and maintain scalable and reliable data pipelines to ingest, transform, and load data from multiple sources.

• Orchestrate and schedule workflows using tools such as Apache Airflow ensuring correct dependencies, retries, alerting, monitoring, and performance.

• Build and maintain data storage solutions, data warehouses and/or data lakes, ensuring data is properly modelled, organized and accessible for analytics and ML use cases.

• Collaborate with data scientists, analysts and other stakeholders to understand data requirements and deliver clean, high-quality data in usable formats.

• Implement data validation, monitoring, and quality controls to guarantee data integrity, consistency and reliability.

• Contribute to productionizing machine learning pipelines — from raw data ingestion through feature engineering, training data preparation, and integration with ML workflows.

• Follow and promote CI/CD best practices for data code and infrastructure (version control, automated tests, deployments, infrastructure as code, etc.).

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  Several years (e.g. 2–5) of professional experience in data engineering or a related role (ETL, data pipelines, data infrastructure).

• Strong proficiency with data orchestration tools such as Apache Airflow (or similar).

• Experience with cloud-based data platforms and warehouses, especially Google BigQuery and/or Databricks

• Excellent SQL skills, and comfortable writing complex queries for large datasets.

• Solid programming skills (e.g. Python) for data processing and transformation.

• Experience working with cloud infrastructure — ideally both on Amazon Web Services (AWS) and Google Cloud Platform (GCP), or willingness and ability to learn them.

• Strong understanding of software engineering practices: version control (e.g. Git), modular code, configuration management, CI/CD for data workloads.

• Strong problem-solving skills, attention to detail, and ability to handle large, complex datasets with performance, scalability and data quality in mind.

Nice-to-Have (Bonus) — but not mandatory

• Familiarity with data governance, data cataloging, metadata management, data lineage — ensuring data quality and traceability.

• Previous exposure to machine learning workflows or model-training pipelines (feature engineering, data versioning, model data pipelines).

• Experience with infrastructure-as-code, automated deployments (Terraform, CloudFormation, etc.), or orchestration beyond just simple pipelines.

• Exposure to cost optimization, data partitioning/indexing, performance tuning of big data workloads.

Our Benefits

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

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