Senior Data Engineer: Real-Time Pipelines & ML (Remote)

NielsenIQ; Ciudad de México; On-site; MXN 1,032,346 - 1,548,520; Full time

Benefits offered by this job

Flexible working environment

Volunteer time off

LinkedIn Learning

Job summary

NielsenIQ is seeking a Sr Data Software Engineer to join their Activate Technology team in CDMX, Mexico. This is a remote position focused on building and operating production-grade data systems.

The ideal candidate will have 3+ years in Data Engineering, proficiency in Python and Scala, and experience with cloud platforms like AWS or Azure. The role involves collaborating with Data Science and evaluating new technologies to improve data ecosystems.

Benefits include a flexible work environment, volunteer time off, and access to LinkedIn Learning.

Qualifications

• 3+ years of hands-on Data Engineering experience.
• Proficient in Python and working knowledge of Scala.
• Expertise with one major cloud provider (AWS, Azure, or GCP).
• Strong experience with Big Data processing (Spark, Databricks).
• Experience with orchestration using Airflow.

Responsibilities

• Own end-to-end data flows from requirements to production operations.
• Design and build scalable batch and real-time data pipelines.
• Partner with Data Science to integrate ML/AI workloads.
• Collaborate with teams to deliver secure and scalable solutions.

Skills

Data Engineering

Python

Scala

AWS/Azure/GCP

Big Data processing (Spark, Databricks)

SQL

Kubernetes

CI/CD practices

LLM workflow frameworks

Data pipelines

Education

B.Sc. or M.Sc. in Computer Science or equivalent

Tools

Airflow

Terraform

MLflow

React

Node.js

Job description

NielsenIQ is seeking a Sr Data Software Engineer to join their Activate Technology team in CDMX, Mexico. This is a remote position focused on building and operating production-grade data systems.

The ideal candidate will have 3+ years in Data Engineering, proficiency in Python and Scala, and experience with cloud platforms like AWS or Azure. The role involves collaborating with Data Science and evaluating new technologies to improve data ecosystems.

Benefits include a flexible work environment, volunteer time off, and access to LinkedIn Learning.