Take technical ownership of a cloud data ecosystem that feeds analytics, machine learning, and commercial decisions for a multinational consumer brand. You'll shape how data moves, scales, and stays trustworthy on Google Cloud, while raising the bar for your team through automation, AI-assisted engineering, and hands‑on mentoring.

What You'd Do:

- Own real-time and scheduled data flows built on BigQuery, Dataflow/Apache Beam, Pub/Sub, Composer, Cloud Run, Cloud Functions, Dataproc, and GCS.
- Define ingestion and transformation strategies (ETL/ELT) for high-volume data in any format.
- Evolve the platform toward decentralized, lakehouse-style architectures that scale with the business.
- Introduce GenAI copilots and AI tooling into the team's daily development work.
- Automate delivery with infrastructure as code (Terraform), version control, and Cloud Build pipelines.
- Prototype AI agents that detect, alert on, and fix pipeline issues with minimal human effort.
- Guarantee data reliability through validation rules, schema change control, and end-to-end traceability.
- Keep cloud spend efficient and systems observable using Stackdriver and Datadog.
- Apply security, permissions, and compliance policies across every data asset.
- Take ideas from early experiments all the way to stable production releases.




- Grow the skills of less experienced engineers through reviews, pair work, and design guidance.
- Work side by side with data science, analytics, and commercial teams to turn their needs into solid technical solutions.

What We're Looking For:

- Bachelor's degree in Computer Science, Software or Systems Engineering, Data Science, Mathematics, or a related field.
- Advanced English (C1/C2) for daily communication.
- +5 years experience building data solutions (data engineering, backend, or architecture), including 4+ years on cloud.
- Strong hands‑on GCP background: BigQuery, Dataflow, Pub/Sub, and Airflow/Composer.
- Experience with Python and SQL.
- Practical experience with Docker, orchestration tools, Terraform, and CI/CD.
- Solid grasp of distributed systems, dimensional modeling, data warehouses, and when to choose streaming over batch.
- Comfortable working in Agile teams.
- Exposure to AI coding assistants, automation, and agent-based architectures.
- Experience guiding or leading engineers.
- PLUS: Google Cloud certification (Data Engineer or Cloud Architect); background in consumer goods, retail, or eCommerce and commercial KPIs; experience with Power BI, Tableau, or Looker.

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📌 Data Engineer Lead (México)
🏢 LaPieza
📍 México