About You

As an Analytics Engineer III on our Data Engineering Team, you will help revitalize our Data services and tooling across our platform with a comprehensive technical strategy to simplify and build scalable systems. This is an exceptional opportunity to shape the future of our platforms and drive meaningful change at scale, making a lasting impact within the automotive industry.

Are you a data platform builder who loves owning things end-to-end? If so — we've got something really exciting for you!

We're on a mission to build something truly foundational at a governed semantic/metrics layer, a data catalog, and a self-service analytics tool that puts the power of data directly into the hands of our business users.

This isn't a maintenance role — this is a build-from-the-ground-up, make-your-mark opportunity!

As our Analytics Engineer, you'll own the infrastructure, deployment, performance, and operations across all three platforms — deciding how each tool gets deployed, secured,

monitored, and tuned for speed, reliability, and cost-efficiency in production. Real ownership. Real impact.

You'll partner closely with our BI, Data Warehouse, Data Science, and ML Engineering teams — all depending on a healthy, well-performing data platform — while working right in the heart of our single source of truth initiative, built from the Data Lake up.This is a broad platform ownership role by design — semantic layer infrastructure,

catalog administration, self-service BI tooling, and warehouse performance tuning all in one. A fast-moving, high-impact environment with a compelling AI roadmap, real-time data ambitions, and the unique challenge of unifying data across multiple platforms

Why You'll Be Excited About This Role

This opportunity enables you to...

- Lead the technical architecture of our semantic and metrics layer, including infrastructure deployment, API design, pre-aggregation strategies,



and enforcing robust authentication and row-level security protocols.
- Manage the core governance infrastructure by administering Atlan—including crawl schedules and AI-driven enrichment—while maintaining the policy center for data access, PII classification, and compliance.
- Oversee the self-service analytics platform operations, focusing on licensing, connection management, and version upgrades, ensuring high-quality platform administration rather than individual content creation.
- Drive Amazon Redshift performance optimization in alignment with the platform, defining and tuning queries to support semantic layer pre-aggregation and business intelligence patterns.
- Assume accountability for platform health, including uptime monitoring, observability alerting, and tracking compute and licensing expenditures across the data stack.
- Provide technical leadership during tool migrations and contribute infrastructure and operability expertise to the evaluation and RFP processes for new semantic and BI technologies.

We're Excited About You Because… (Must-have)

- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Five plus years of experience in data engineering or platform engineering, with
- meaningful ownership of production data infrastructure.
- Deep, hands-on experience tuning Amazon Redshift for performance —
- distribution/sort key design and compression encoding, WLM or
- concurrency-scaling/Serverless configuration, materialized views and result




- caching for query acceleration, and reading/optimizing execution plans. This is a
- hard requirement.
- Experience administering a data catalog or governance platform — Atlan,
- Collibra, Alation, DataHub, or similar.

Bonus:

- Experience administering an enterprise BI or self-service analytics platform — Tableau Server/Cloud, Looker, Sigma, Omni, Power BI, or similar — including licensing, security model, and workspace/connection management.
- Experience with a semantic layer, metrics layer, or query acceleration tool (Cube, Omni, dbt Semantic Layer, AtScale, LookML, or comparable), or a demonstrated ability to ramp quickly on a new one given the Redshift and platform-administration depth above.
- Solid understanding of API layer design, authentication/authorization patterns, and row-level security implementation.
- Experience with observability and monitoring tooling — Datadog, Metaplane, CloudWatch, or similar — including setting up alerting and being accountable for uptime.
- Expertise in SQL or similar query languages (PL/SQL, DDL, HiveQL, or SparkSQL) for complex data manipulation.
- Strong programming skills in Python, Scala, or Java, with a focus on automation and engineering efficiency.
- Experience managing source code via GitHub and architecting CI/CD pipelines for data using Jenkins, GitHub Actions, or CircleCI.
- Prior experience owning three or more of these tool categories (catalog, semantic layer, BI platform, warehouse performance) simultaneously on a lean team.
- Experience supporting a BI platform migration (e.g., moving from one self-serve tool to another) from the infrastructure side.
- Experience optimizing cloud data warehouse costs at scale (Redshift, Snowflake, or BigQuery).
- Direct production experience with Cube.dev, Omni, or a comparable semantic layer product specifically.

📌 Analytics Data Platform Engineer (Ciudad de México)
🏢 Coforge
📍 Ciudad de México