Senior Data Engineer II

RELX; Ciudad de México; Presencial; MXN 1,098,000 - 1,465,000; Jornada completa

Descripción de la vacante

A global leader in information and analytics in Mexico City is seeking a Senior Data Engineer to build scalable data solutions. This includes designing data architectures and developing ETL/ELT pipelines. The ideal candidate has 5+ years of experience in data engineering, expertise in Python and SQL, and thrives in a collaborative environment. Benefits include a private medical plan and life insurance.

Servicios

Private Medical/Dental Plan

Savings Fund

Life Insurance

Meal/Grocery Voucher

Formación

• 5+ years of experience in data engineering or related field.
• Expert proficiency in Python for data engineering, ELT development, and automation.
• Strong SQL skills with experience in query optimization and performance tuning.

Responsabilidades

• Design and maintain scalable data architectures.
• Develop ETL/ELT pipelines and implement DataOps practices.
• Mentor junior engineers and collaborate with stakeholders.

Conocimientos

Python for data engineering

SQL

Snowflake

AWS Glue

Apache Airflow

DataOps

CI/CD pipelines

Data modeling principles

Problem-solving

Strong communication skills

Educación

Bachelor's Degree in Computer Science

Herramientas

AWS S3

Kafka

Terraform

Git

Docker/Kubernetes

Descripción del empleo

About Us

Working in data engineering at Elsevier means your work truly matters — it powers the insights that drive healthcare, education, and scientific discovery. As a Senior Data Engineer, you’ll help build the foundation for data‑driven decision making across the organization, collaborating with teams to deliver scalable, secure, and reliable data solutions.

About the Team

We are a collaborative, forward‑thinking data engineering team focused on building modern cloud‑based data platforms and pipelines. Our work spans Python, SQL, Snowflake, AWS, Airflow, and other cutting‑edge technologies. We take pride in delivering robust architectures, implementing DataOps best practices, and mentoring others. We work closely with business partners in the U.S., and time‑zone overlap is key to our success. This role supports long‑term strategic goals, transitioning from contractor‑led efforts to full‑time ownership that strengthens our internal capabilities and ensures sustainable growth.

About the Role

We’re looking for a Senior Data Engineer who thrives in inclusive, collaborative environments and is passionate about building scalable data solutions. You’ll design and maintain data architectures, develop ETL/ELT pipelines, and implement DataOps practices. You’ll mentor junior engineers and work closely with stakeholders to translate business needs into technical solutions.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Python, Snowflake, AWS Glue, and Airflow.
• Build and optimize ETL/ELT workflows to ingest, transform, and deliver data from various sources.
• Implement data quality checks, monitoring, and alerting to ensure pipeline reliability.
• Collaborate with analysts, scientists, and stakeholders to understand requirements and deliver solutions.
• Establish and enforce data engineering best practices, coding standards, and design patterns.
• Optimize query performance and data storage strategies in Snowflake and cloud data warehouses.
• Implement CI/CD pipelines for automated testing and deployment of data workflows.
• Monitor pipeline performance, troubleshoot issues, and implement improvements proactively.
• Create and maintain technical documentation for data architectures, pipelines, and processes.
• Participate in code reviews and provide constructive feedback to team members.
• Mentor junior data engineers on modern tools, techniques, and best practices.
• Stay current with emerging data technologies and evaluate their applicability to business needs.
• Collaborate with DevOps and platform teams to ensure infrastructure scalability and reliability.
• Support data governance initiatives and ensure compliance with security policies.

Requirements

• 5+ years of experience in data engineering or related field.
• Bachelor's Degree in Computer Science, Engineering, or equivalent practical experience.
• Expert proficiency in Python for data engineering, ELT development, and automation.
• Strong SQL skills with experience in query optimization and performance tuning.
• Hands‑on experience with Snowflake (SnowSQL, stored procedures, streams/tasks).
• Proficiency with AWS data services: Glue, S3, Lambda, Redshift.
• Experience with Apache Airflow or similar orchestration tools (Luigi, Prefect, Dagster).
• Knowledge of data modeling principles (dimensional modeling, data vault, normalization).
• Experience with streaming technologies (Kafka, Kinesis) and dbt for analytics engineering.
• Understanding of DataOps, CI/CD for data pipelines, and infrastructure as code (Terraform).
• Familiarity with version control (Git), code reviews, and collaborative development.
• Knowledge of data quality frameworks (Great Expectations) and containerization (Docker/Kubernetes) is a plus.
• Understanding of data governance, security best practices, and compliance requirements.
• Strong problem‑solving skills and ability to research new technologies independently.
• Excellent communication skills for technical and non‑technical audiences.

Working for You

We care about your wellbeing and success. Here are some of the benefits we offer:

• Private Medical/Dental Plan
• Savings Fund
• Life Insurance
• Meal/Grocery Voucher

About the Business

Elsevier is a global leader in information and analytics, helping researchers and healthcare professionals advance science and improve health outcomes. We combine quality content with powerful technology to support education, research, and clinical decision‑making. Join us.

Equal Opportunity Statement

We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.

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