Regional Data Engineer - End-to-End Data Pipelines

Chubb Life Fund; México; A distancia; MXN 420.000 - 660.000; Jornada completa

Descripción de la vacante

Chubb Life Fund is seeking a Data Engineer to design, build, and maintain end-to-end data pipelines powering analytics and data products. You will implement batch and streaming ETL/ELT workflows on Databricks, transform raw data into well-modeled datasets, and optimize for performance and cost as data volumes grow.

The role requires end-to-end ownership from ingestion to consumption by analysts and data scientists, with collaboration across business stakeholders to translate requirements into

Formación

• 3+ years of experience in data engineering or a comparable role.
• Strong Python for data processing, automation, and pipeline development.
• Advanced SQL with complex joins, window functions, and optimization.
• Hands-on Databricks and PySpark in a production environment.
• Experience designing and operating ETL/ELT pipelines at scale.
• Understanding of data warehousing and dimensional modeling.
• Experience with Git and collaborative development workflows.

Responsabilidades

• Design, build, and maintain batch and streaming ETL/ELT pipelines.
• Model data across raw, cleansed, and curated layers with Delta Lake.
• Ingest data from relational databases, APIs, files, and event streams.
• Tune Spark jobs and SQL for performance and cost.
• Build data quality checks and monitoring to catch issues early.
• Orchestrate and schedule workflows with retry and alerting.
• Apply software engineering practices to data work and deployments.
• Collaborate with analysts, data scientists, and stakeholders to translate requirements.
• Document pipelines, data lineage, and design decisions.

Conocimientos

Python

SQL

PySpark

Databricks

ETL/ELT

Data modeling

Git

Herramientas

Databricks

Delta Lake

Airflow

CI/CD

dbt

Descripción del empleo

Chubb Life Fund is seeking a Data Engineer to design, build, and maintain end-to-end data pipelines powering analytics and data products. You will implement batch and streaming ETL/ELT workflows on Databricks, transform raw data into well-modeled datasets, and optimize for performance and cost as data volumes grow.

The role requires end-to-end ownership from ingestion to consumption by analysts and data scientists, with collaboration across business stakeholders to translate requirements into