Data Engineer Lead

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.