Staff Data Engineer – Data Platform & Pipelines Lead

Meeru AI Inc; México; On-site; MXN 900,000 - 1,350,000; Full time

Job summary

Meeru AI Inc seeks a Staff Data Engineer to own major data foundation subsystems—pipelines, connectors, and curated models feeding analytics and AI layers. You’ll implement robust, scalable data solutions with a bias toward correctness and reproducibility.

You’ll work hands-on with Snowflake, BigQuery, and other warehouses, ensuring performance and reliability while coordinating with backend/AI teams on data contracts in a multi-cloud environment.

Qualifications

• 7+ years in data engineering and ownership of production pipelines.
• Expert SQL and data modeling for cloud warehouses.
• Real dbt production experience with incremental models.
• Production orchestration using Airflow or Dagster.
• Deep understanding of warehouse internals and performance tuning.
• Commitment to correctness: tests, lineage, idempotent pipelines.
• Solid Python for pipeline tooling and testing.
• Experience integrating varied data sources with stability.

Responsibilities

• Own end-to-end data pipelines and curated models feeding analytics and AI layers.
• Collaborate with backend and AI teams, defining data contracts and governance.
• Ensure data quality, lineage, tests, and reproducibility across systems.
• Mentor junior engineers and review code for maintainability.

Skills

7+ yrs data eng

SQL & data modeling

dbt production

Airflow / Dagster

Warehouse performance

Data quality & lineage

Python scripting

Data integration

Tools

Snowflake

BigQuery

PostgreSQL

dbt

Airflow

Dagster

Job description

Meeru AI Inc seeks a Staff Data Engineer to own major data foundation subsystems—pipelines, connectors, and curated models feeding analytics and AI layers. You’ll implement robust, scalable data solutions with a bias toward correctness and reproducibility.

You’ll work hands-on with Snowflake, BigQuery, and other warehouses, ensuring performance and reliability while coordinating with backend/AI teams on data contracts in a multi-cloud environment.