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.

Job Description

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.

Key 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 integral teams in a fast-paced environment

Qualifications
- 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)

Preferred Qualifications
- Experience with
Spark / PySpark
- Familiarity with orchestration tools such as
Airflow
- Knowledge of
DBT or similar transformation tools
- Experience working with
large-scale da

📌 Data Engineer (Ciudad de México)
🏢 Nielseniq
📍 Ciudad de México