Data Engineer

At NielsenIQ, we deliver the most complete and clear understanding of consumer buying behavior that reveals new pathways to growth. We are looking to add a Data Engineer to our Label Insight team.

Label Insight plays a crucial part in how we digitize, enhance and distribute data to clients and the wider NielsenIQ business. To help achieve this, we work with open data ecosystems in the cloud. Our clients around the world rely on NielsenIQ’s data and insights to innovate and grow.

As a Data Engineer, you’ll be part of a team of smart, highly skilled technologists who are passionate about supporting and progressing leading edge solutions to meet our business requirements.

Responsibilities

Help establish Data Engineering best practices with Label Insight domain; Design, develop, and implement end-to-end ETL and ELT pipelines; Create and improve complex queries and data transformation operations; Collaborate with stakeholders to design, develop and implement data extraction and reporting solutions (define requirements, refine, etc.) that best match their needs.; Supporting business functions to maximize the value of their data assets through visualizations and reporting tools such as Looker and Power BI.

Requirements

Experience with modern data tools (e.g. Snowflake, Airflow, dbt) and cloud environments; Strong programming (esp. Python) and SQL skills; Knowledge of engineering best practices: CI/CD, testing, version control, infrastructure as code; Strong data modeling skills; Understanding of both relational and graph databases; Familiarity with building for agentic data flows; Experience with various analytical data platforms and technologies; Experience with Looker, Power BI, or other data visualization platforms; Experience in custom or structured data integration design, implementation, and maintenance; Degree in Computer Science, Engineering (or equivalent combination of skills and experience); 3+ years working within a data engineering/reporting environment

Benefits

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