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Data Engineer

NielsenIQ nielseniq.com Open · verified Oct 24, 2026
Hybrid Mexico City Full-time Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at NielsenIQ. Mexico City · full-time.

Pay not stated Data Engineer salary

RoleData Engineering
SeniorityMid-level
LocationMexico City
WorkplaceHybrid
EmploymentFull-time
PostedJun 19, 2026 · 4mo ago
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Build and tune ETL/ELT flows that ingest, transform and deliver large datasets
  • Check data for accuracy and consistency throughout pipeline stages, then investigate failures across systems
  • Turn stakeholder data needs into technical solutions and contribute to star-schema or dimensional modeling
  • Improve pipeline speed and reduce delays while keeping data dependable for analytics

What you bring

  • You have two to four years in data engineering or a related role
  • Python and SQL proficiency are required, along with hands-on work on data pipelines and ETL
  • You can work in English with global teams

Who this fits

This mid-level role suits an engineer who can work independently, communicate across teams and handle data quality details. It is hybrid in Mexico City and calls for collaboration with global teams.

From the employer

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.

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 global teams in a fast-paced environment
  • 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 datasets
  • Exposure to CI/CD or DataOps practices

What You’ll Need to Succeed

  • Strong attention to detail and data quality
  • Hands-on mindset with ability to learn quickly
  • Ownership of tasks and ability to work independently
  • Good communication and collaboration skills
  • Interest in building scalable data 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

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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

Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Engineering

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.