Senior/Lead Data Engineer – AI-Native Aftermarket Platform | Mexico
Remote · Mexico City, Mexico City, Mexico
Job Summary
Senior/Lead Data Engineer to design and scale data pipelines powering an AI-native aftermarket platform. Responsibilities include designing robust end-to-end data pipelines, star and snowflake schemas, and production-grade Python code; building and testing dbt models across staging, intermediate, and mart layers; deploying Databricks Asset Bundles and ensuring data quality and governance; mentoring mid-level engineers, defining architectural direction, and participating in hiring panels. Key skills include SQL and dimensional modeling, PySpark, Delta Lake features, dbt, Databricks, Python with testing and type hints, Git workflows, secret management, and Azure data tooling. The role emphasizes architectural leadership, cross-repository governance, and coupling data work with business metrics in collaboration with AI-driven platforms.
Required Qualifications
- SQL and dimensional modeling (medallion architecture, SCDs, grain management)
- Incremental/checkpoint/replaceWhere data pipelines
- Production-grade Python with type hints, pytest, and ruff
- Spark/PySpark diagnostic and debugging
- Delta Lake features (MERGE, OPTIMIZE, Z-ORDER, time travel)
- dbt (models, tests, exposures)
- Databricks Asset Bundles (DAB) and Unity Catalog
- Data quality checks pre-write asserts and schema checks
- Git workflows, conventional commits, and documentation practices
- Secret management tools (Azure Key Vault, Databricks secret scopes)
- Reading/editing GitHub Actions workflows for Databricks deployment
- Reading/modifying Azure Data Factory pipelines and Azure Data Lake storage (highly preferred)
- Awareness of PII detection and masking best practices
- Multi-tenant configuration patterns to onboard tenants with zero code changes
- Proficiency with AI-assisted development tools (e.g., Claude Code)
- Incident post-mortems and feature handovers with Data Science teams
- Strong technical communication for PRs and runbooks
- Leading technical initiatives and architectural standards
- Ability to mentor mid-level engineers and participate in hiring panels
- Experience designing data architectures and setting standards across core data systems
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