This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. Analytics Engineer - Data Platform based in Mexico.
As a Sr. Analytics Engineer - Data Platform, you will own how data is structured, defined, trusted, and delivered across the organization. You’ll design data contracts and analytical models that ensure critical metrics remain consistent across channels and teams. The role combines hands-on analytics engineering with ownership of ingestion, orchestration, quality, observability, and documentation. You’ll work closely with product, business, engineering, and data teams while setting technical standards and mentoring others. A key part of your impact will be enabling genuine self-service analytics while maintaining highly reliable data products and reporting. You’ll also help create the foundation for predictive models and machine learning capabilities to move from exploration into production.
Accountabilities:
You’ll take ownership of the analytical data foundation, balancing technical excellence, reliability, and business impact. Your responsibilities will include:
- Design and operate data contracts for critical metrics and datasets, partnering with domain owners and maintaining versioned definitions, tests, commits, and catalogs in dbt.
- Own analytical data modeling, including data layers, conventions, and dimensional models, supported by documentation and CI processes that prevent technical debt.
- Strengthen the data platform across ingestion, orchestration, quality, and observability using technologies such as Airbyte and Dagster.
- Build monitoring and quality processes that identify anomalies proactively before they affect stakeholders or reporting.
- Enable true self-service analytics through semantic layers and models in tools such as Omni and Hex, helping teams answer questions independently while maintaining strong data standards.
- Deliver high-confidence dashboards and reports for leadership, external partners, and regulatory reporting where accuracy and reliability are critical.
- Work closely with product and business domains while contributing to cross-functional standards for data contracts, quality, and modeling.
- Raise the technical bar through code reviews, pairing, mentoring, reusable practices, and engineering standards that remain sustainable across the team.
- Enable Data Science and Machine Learning initiatives by developing reliable datasets, reusable features, and production-ready pipelines that allow models and predictions to reach the product.
Requirements:
You’ll bring strong analytical engineering and data platform expertise, combined with sound engineering practices and the ability to translate ambiguous business questions into trusted data definitions. The ideal profile includes:
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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