Data Engineer Lead

Lapieza; Ciudad de México; Presencial; MXN 700.000 - 950.000; Jornada completa

Descripción de la vacante

Lapieza is seeking a senior data engineer to take technical ownership of a cloud data ecosystem that fuels analytics, ML, and commercial decisions. You will shape how data moves, scales, and stays trustworthy on Google Cloud, while raising the bar for the team through automation and AI-assisted engineering.

You will own real-time and scheduled data flows using BigQuery, Dataflow, Pub/Sub, and Airflow/Composer, implement ETL/ELT strategies, and guide engineers toward scalable lakehouse

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

Data engineering

Cloud architecture

GCP

Python

SQL

Docker

Terraform

CI/CD

Distributed systems

Agile

Educación

Bachelor's degree in Computer Science / Software / Systems Engineering

Herramientas

Airflow/Composer

BigQuery

Dataflow

Pub/Sub

Cloud Run / Cloud Functions

Dataproc

Descripción del empleo

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.