Senior Data Engineer (supply chain)

Cognite
Bengaluru
Full timeFunction: Supply Chain & LogisticsExperience: 3-7 yearsSkills: ["Ownership","Problem-solving","Technical consulting","Cross-functional collaboration","Product-quality focus"]

Design and package scalable “Data Pipelines” that integrate internal SAP/ERP systems with supply-chain logistics visibility platforms and market intelligence sources. Optimize and curate ingested data for CDF knowledge graph consumption, enhance an integrated supply chain solution model, and build high-performance ETL and semantic/ontology layers that are “agent-ready” for ATLAS AI reasoning workflows. Partner with Product, Value Delivery, and ecosystems (e.g., FourKites/Project44, AWS) to deliver robust, well-documented connectors and models.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Cognite
Cognite
2 months ago

Senior Data Engineer (supply chain)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 40 minutes agoStatus: Live

Job Summary

Design and package scalable “Data Pipelines” that integrate internal SAP/ERP systems with supply-chain logistics visibility platforms and market intelligence sources. Optimize and curate ingested data for CDF knowledge graph consumption, enhance an integrated supply chain solution model, and build high-performance ETL and semantic/ontology layers that are “agent-ready” for ATLAS AI reasoning workflows. Partner with Product, Value Delivery, and ecosystems (e.g., FourKites/Project44, AWS) to deliver robust, well-documented connectors and models.
Location: Bengaluru
Employment Type: Full time
Job Function: Supply Chain & Logistics
Seniority: Mid level

Key Responsibilities

  • •Architect and package scalable data pipelines to ingest, normalize, and integrate supply-chain data from internal ERP/MES and external logistics/market intelligence sources.
  • •Optimize the integrated supply chain solution model by defining and packaging relationships between disparate source data points for knowledge graph traversal.
  • •Build and enhance knowledge graph structures in CDF so AI agents can navigate from notifications (e.g., delayed shipments) to impacted work orders or schedules.
  • •Lead Advanced DataOps: design high-performance ETL with Python/SQL/REST APIs, including semantic ontology and transforms to make industrial time-series/contextual events “agent-ready”.
  • •Collaborate with Product, Value Delivery, and partners to ensure integrations are robust and aligned to standards; lead discovery/design sessions and troubleshoot pipeline/data quality issues.

Key Requirements

  • •3–7 years’ experience in data-intensive, customer-facing work building production-grade pipelines.
  • •Strong external API integration experience with REST APIs for logistics visibility and market intelligence data sources.
  • •Deep supply chain domain knowledge across TMS, WMS, and SAP procurement/production/maintenance modules (or similar ERP/Supply Planning suites).
  • •Expertise in knowledge graph and relational modeling, optimizing schemas for graph traversals and relational queries.
  • •Proficiency in Python and SQL, cloud-native development (AWS, GCP, or Azure), and familiarity with big data/database systems (e.g., Oracle, MS SQL).
Experience:3-7 yearsSupply chainKnowledge graphETLData engineeringCustomer-facingLogistics visibilitySAP/ERPCloud-native
Skills:OwnershipProblem-solvingTechnical consultingCross-functional collaborationProduct-quality focus
Languages:English
Tech Stack:PythonSQLREST APIsAWSGCPAzureGitCI/CDCognite Data Fusion (CDF)Cognite Data ObjectsIndustrial DataOpsATLAS AIOCRDocument AILLM-based extractionBig DataOracleMS SQLSAPERP

Company Brief

Cognite
Provides industrial data software that helps companies connect, contextualize, and use operational data for analytics, AI, and digital transformation. Its platform is used by heavy-industry customers to improve asset performance and operations.
Industry: Data Infrastructure
Company Size: Large (251 to 1,000 employees)
Growth: Scaleup
Headquarters: Oslo, Norway
Founded: 2016
WebsiteLinkedIn