This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Data Engineer (Ingeniero de Datos Senior) in Mexico.

In this role, you will architect, develop, and optimize scalable data pipelines to support advanced analytics and machine learning initiatives. You will work closely with cross-functional teams to ensure high-quality, reliable, and secure data infrastructure across the organization. The role involves improving performance of existing systems, implementing best practices in data architecture and governance, and enabling data-driven decision-making. You will have the opportunity to mentor junior engineers, shape technical direction, and work in a collaborative, fast-paced environment where your contributions directly impact strategic outcomes. This is ideal for proactive engineers passionate about modern data solutions and high-impact projects.

Accountabilities:

Design, build, and maintain scalable, secure ETL pipelines to support machine learning and analytics workflows.
Optimize data collection, ingestion, and transformation processes for batch and real-time systems.
Ensure data quality, accuracy, and reliability across pipelines while enforcing governance and compliance standards.
Collaborate with Data Scientists, MLOps, and other teams to enable model development, deployment, and feature engineering.
Manage connectivity with BI tools, databases, data warehouses, and cloud platforms.
Mentor junior engineers, participate in code reviews, and promote engineering excellence.
Document processes, contribute to team knowledge sharing, and support continuous improvement initiatives.

Requirements

Bachelor’s degree in Data Engineering, Data Science, Computer Science, or related field with 5+ years of relevant experience; Master’s degree with 3+ years experience is also acceptable.
Proven experience with big data platforms (e.g., Spark, Hadoop, AWS S3) and advanced proficiency in SQL (SQL Server, MySQL, Oracle).
Hands-on experience designing ETL pipelines, data warehousing solutions, and supporting ML or data science teams.
Familiarity with MLOps tools (MLflow, Airflow, Kubeflow) and cloud platforms such as Databricks or Snowflake is a plus.
Strong understanding of data modeling for ML, feature store management, and serving strategies.
Experience with version control, CI/CD pipelines, and data testing frameworks.
Bilingual in English and Spanish, with excellent communication and collaboration skills.
Highly analytical, detail-oriented, self-organized, and capable of working in agile environments.

Benefits

Competitive salary: $45,000–$50,000 MXN per month (depending on experience and qualifications).
Fully remote work option or office-based in Mexico City.
Comprehensive benefits package covering health, dental, and vision needs.
Opportunities for professional development and career growth.
Collaborative, high-impact, and fast-paced work environment.
Mentorship and learning opportunities within a multidisciplinary data team.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the three candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

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