Data Engineer

NielsenIQ (NIQ) is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior. With operations in more than 90 countries, NIQ provides manufacturers and retailers with accurate, actionable insights to innovate and grow.

We are looking for a talented Data Engineer to join our global data engineering team. In this role, you will be responsible for building and maintaining scalable data pipelines and supporting the delivery of high-quality data for analytics and business insights.

You will work closely with cross-functional teams to ensure data availability, reliability, and performance across our platforms.

Responsibilities

Build, maintain, and optimize data pipelines (ETL/ELT) for large-scale datasets; Develop scalable data solutions for data ingestion, transformation, and delivery; Ensure data quality, validation, and reliability across pipelines; Work with stakeholders to understand data needs and translate them into technical solutions; Debug and troubleshoot data issues across pipelines and systems; Support data modeling efforts (e.g., star schema, dimensional models ); Contribute to improving pipeline performance and reducing latency; Collaborate with global teams in a fast-paced environment

Requirements

2–4 years of experience in Data Engineering or related roles; Strong programming skills in Python and SQL (required); Experience working with data pipelines and ETL processes; Familiarity with cloud platforms (Azure, AWS, or GCP); Experience with data warehousing solutions (Snowflake, Redshift, BigQuery, etc.); Understanding of data modeling concepts; Strong problem-solving and debugging skills; Ability to work in a global environment (English required)

Nice to have

Experience with Spark / PySpark; Familiarity with orchestration tools such as Airflow; Knowledge of DBT or similar transformation tools; Experience working with large-scale datasets; Exposure to CI/CD or DataOps practices

Benefits

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