Lead Applications Developer GCP BigQuery Pub Sub Kafka GKE Java Python C

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Découvrez votre prochaine opportunité au sein dune organisation qui compte parmi les 500 plus importantes entreprises mondiales. Envisagez des opportunités innovantes, découvrez notre culture enrichissante et travaillez avec des équipes talentueuses qui vous poussent à vous développer chaque jour. Nous savons ce qu’il faut faire pour diriger UPS vers lavenir : des personnes passionnées dotées d’une combinaison unique de compétences. Si vous avez les qualités, de la motivation, de lautonomie ou le leadership pour diriger des équipes, il existe des postes adaptés à vos aspirations et à vos compétences daujourdhui et de demain.

Job Summary

Fiche de poste :

We are seeking a GCP-focused Data Engineer to build scalable, high‑quality data pipelines supporting our Data Maturity initiative for Logistics/Parcel Services. The ideal candidate has strong experience in GCP data services, data modeling, data quality frameworks, and understands logistics domain data such as shipment tracking, routing, and warehouse operations.

Key Responsibilities

Core Engineering (All Levels)

• Pipeline Development: Design and develop scalable ETL/ELT pipelines using BigQuery, Pub/Sub, and Dataflow/Dataproc.
• Microservices: Build and deploy APIs using Python/Java/C# to integrate enterprise and external logistics systems.
• Orchestration: Orchestrate workloads via Composer (Airflow) or GKE using Docker and Kubernetes.
• Data Quality: Implement validation checks, lineage tracking, and monitoring for pipeline SLAs (freshness, latency).
• Modeling: Model logistics and supply chain data in BigQuery for analytics and operational insights.
• DataOps: Apply CI/CD, automated testing, and versioning best practices.
  
  

• System Design: Take ownership of end-to-end technical design for complex data modules.
• Mentorship: Actively mentor junior engineers and conduct rigorous code reviews to ensure high engineering standards.
• Best Practices: Establish and document DataOps standards and reusable patterns for the team.
  
  

• POD Leadership: Act as the technical head of the data pod, ensuring sprint goals are met and unblocking the team.
• Architecture: Define the high-level architecture and long-term technical roadmap for the logistics data platform.
• Stakeholder Management: Partner with business leaders to translate complex logistics requirements into technical specifications.
• Negotiation: Manage requirements scoping and prioritize backlogs by balancing technical debt with business value.
• Coaching: Drive the professional growth of the entire engineering team through structured coaching and performance feedback.
  
  

• Relevant experience –
  
  

• Strong hands‑on experience with GCP BigQuery, Pub/Sub, GCS, Dataflow/Dataproc.
• Proficiency in Python/Java/C#, RESTful APIs, and microservice development.
• Experience with Kafka for event-driven ingestion.
• Strong SQL and experience with data modeling
• Expertise in Docker/Kubernetes (GKE) and CI/CD tools (Cloud Build, GitHub Actions, or ADO).
• Experience implementing Data Quality, Metadata management, and Data Governance frameworks.
  
  

• Experience with Terraform, Cloud Composer (Airflow)
• Experience in Azure Databricks, Delta Lake, ADLS, and Azure Data Factory
• Experience in Knowledge Graph Engineering using Neo4j and/or Stardog
• Familiarity with Data Governance tools or Cataloging systems (AXON Informatica)
• Logistics domain experience
  
  

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field