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Lead Data Engineer Telecom Supply Chain
1 month ago
Job Description: Lead Data Engineer Telecom Supply ChainWork type: ContractPosition OverviewWe are seeking an experienced Lead Data Engineer to design, build, and optimize scalable data solutions for our Telecom Supply Chain analytics and operations platform. The ideal candidate will bring deep technical expertise in Apache Spark, Scala, Python, Azure, and Databricks, along with strong domain knowledge of telecom supply chain processes such as inventory management, logistics, fulfillment, and device lifecycle management.Key ResponsibilitiesData Architecture & EngineeringDesign and develop end-to-end data pipelines leveraging Apache Spark, Scala, and Python for large-scale processing.Architect and maintain data lake and data warehouse solutions on Azure and Databricks.Implement robust ETL/ELT processes for ingesting structured, semi-structured, and unstructured data from diverse telecom supply chain systems (SAP, Oracle ERP, logistics feeds, etc.).Drive best practices in data modeling, partitioning, and schema design to support analytical workloads.Performance OptimizationOptimize Spark jobs for performance, scalability, and cost-efficiency.Monitor and fine-tune Azure Data Lake Storage, Synapse, and Databricks environments for reliability and throughput.Implement CI/CD pipelines for automated testing and deployment of data solutions.Collaboration & Cross-functional IntegrationWork closely with supply chain planners, logistics teams, and ERP specialists to ensure data accuracy and integrity.Collaborate with data analysts and visualization teams to deliver real-time insights into demand forecasting, inventory optimization, and device lifecycle tracking.Required Technical SkillsSkill AreaProficiency RequiredProgramming LanguagesAdvanced in Scala, Python, SQLBig Data FrameworksExpert in Apache Spark, experience with Delta LakeCloud PlatformsHands-on with Microsoft Azure (Data Lake, Synapse, Data Factory)Data PlatformsDatabricks advanced experience in workspace configuration, notebooks, clustersETL ToolsStrong experience with Azure Data Factory, Airflow, or equivalent orchestration toolsVersion Control & CI/CDGit, Azure DevOps, JenkinsDatabase SystemsSQL Server, Oracle, Snowflake (preferred)Data ModelingDimensional modeling, Data Vault, or similar methodologiesPerformance OptimizationSpark tuning, cluster scaling, data partitioning strategiesDomain ExpertiseDeep understanding of Telecom Supply Chain operations, including:Device procurement and logisticsInventory and warehouse managementOrder fulfillment and reverse logisticsNetwork asset lifecycle and configuration dataFamiliarity with ERP systems (SAP ABAP, Oracle ERP) and their integration with data platforms.QualificationsBachelors or Masters degree in Computer Science, Data Engineering, or a related field.8+ years of experience in data engineering, with at least 3+ years leading data teams.Proven experience delivering enterprise-grade data solutions in a cloud-native, large-scale environment.Strong analytical, problem-solving, and communication skills.Telecom or Supply Chain project experience is mandatory.Preferred QualificationsAzure Data Engineer or Databricks certification.Experience with real-time streaming (Kafka, Event Hubs).Exposure to machine learning pipelines and MLOps integration.Familiarity with Agile delivery and DevOps practices.
