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 Big Query, 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 Gen AI 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 : Big Query, 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 e Commerce and commercial KPIs; experience with Power BI, Tableau, or Looker. #J-18808-Ljbffr

📌 Data engineer lead (Tijuana)
🏢 LaPieza
📍 Tijuana