{"id":1606553,"url":"https://alion.io/job/ups-lead-applications-developer-gcp-bigquery-pubsub-kafka-gke-javapythonc","title":"Lead Applications Developer – GCP, BigQuery, Pub/Sub, Kafka, GKE, Java/Python/c#","company":{"id":37664,"name":"UPS","domain":"ups.com","url":"https://alion.io/company/ups","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Phenom","truth_index":{"grade":"A","score":98,"open_postings":371,"ghost_share":0.038,"stale_share":0.032,"repost_share":0.24,"time_to_fill_p50_days":9,"computed_at":"2026-10-21T05:46:15Z"}},"role":"Backend","role_family":"Backend","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":19500,"max_usd":55000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":12},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"C#","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Google GKE","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"Parcel","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Azure","optional":true},{"name":"Azure Data Factory","optional":true},{"name":"Databricks","optional":true},{"name":"Delta Lake","optional":true},{"name":"Informatica","optional":true},{"name":"JavaScript","optional":true},{"name":"Knowledge Graph","optional":true},{"name":"Neo4j","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-09-16T00:00:00Z","employer_posted_date":"2026-10-02","last_verified_at":"2026-10-21T23:27:39Z","board_verified":true,"closed_at":null,"days_open":36,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":36},"description":"Before you apply to a job, select your language preference from the options available at the top right of this page.\nExplore your next opportunity at a Fortune Global 500 organization. Envision innovative possibilities, experience our rewarding culture, and work with talented teams that help you become better every day. We know what it takes to lead UPS into tomorrow-people with a unique combination of skill + passion. If you have the qualities and drive to lead yourself or teams, there are roles ready to cultivate your skills and take you to the next level.\nJob Description:\nJob Summary:\nWe 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.\nKey Responsibilities:\nCore Engineering (All Levels)\nPipeline Development: Design and develop scalable ETL/ELT pipelines using BigQuery, Pub/Sub, and Dataflow/Dataproc.\nMicroservices: Build and deploy APIs using Python/Java/C# to integrate enterprise and external logistics systems.\n Orchestration: Orchestrate workloads via Composer (Airflow) or GKE using Docker and Kubernetes.\n Data Quality: Implement validation checks, lineage tracking, and monitoring for pipeline SLAs (freshness, latency).\nModeling: Model logistics and supply chain data in BigQuery for analytics and operational insights.\nDataOps: Apply CI/CD, automated testing, and versioning best practices.\nIntermediate / Senior additions\nSystem Design: Take ownership of end-to-end technical design for complex data modules.\nMentorship: Actively mentor junior engineers and conduct rigorous code reviews to ensure high engineering standards.\nBest Practices: Establish and document DataOps standards and reusable patterns for the team.\nLead additions\nPOD Leadership: Act as the technical head of the data pod, ensuring sprint goals are met and unblocking the team.\nArchitecture: Define the high-level architecture and long-term technical roadmap for the logistics data platform.\nStakeholder Management: Partner with business leaders to translate complex logistics requirements into technical specifications.\nNegotiation: Manage requirements scoping and prioritize backlogs by balancing technical debt with business value.\nCoaching: Drive the professional growth of the entire engineering team through structured coaching and performance feedback.\nRequired Skills:\nRelevant experience -\nLead - Min 7+ yrs of relevance experience\nStrong hands-on experience with GCP BigQuery, Pub/Sub, GCS, Dataflow/Dataproc.\nProficiency in Python/Java/C#, RESTful APIs, and microservice development.\nExperience with Kafka for event-driven ingestion.\nStrong SQL and experience with data modeling\nExpertise in Docker/Kubernetes (GKE) and CI/CD tools (Cloud Build, GitHub Actions, or ADO).\nExperience implementing Data Quality, Metadata management, and Data Governance frameworks.\nPreferred Qualifications:\nExperience with Terraform, Cloud Composer (Airflow)\nExperience in Azure Databricks, Delta Lake, ADLS, and Azure Data Factory\nExperience in Knowledge Graph Engineering using Neo4j and/or Stardog\nFamiliarity with Data Governance tools or Cataloging systems (AXON Informatica)\nLogistics domain experience\nEducation\nBachelor’s degree in Computer Science, Information Systems, Engineering, or related field\n Employee Type:\nPermanentUPS is committed to providing a workplace free of discrimination, harassment, and 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