Lead Data Engineer Telecom Supply Chain

5 days ago

Burnaby, Canada Burgeon IT Services Full time

Job Description: Lead Data Engineer Telecom Supply Chain Work type: Contract Position Overview We 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 Responsibilities Data Architecture & Engineering Design 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 Optimization Optimize 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 Integration Work 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 Skills Skill Area Proficiency Required Programming Languages Advanced in Scala, Python, SQL Big Data Frameworks Expert in Apache Spark, experience with Delta Lake Cloud Platforms Hands-on with Microsoft Azure (Data Lake, Synapse, Data Factory) Data Platforms Databricks advanced experience in workspace configuration, notebooks, clusters ETL Tools Strong experience with Azure Data Factory, Airflow, or equivalent orchestration tools Version Control & CI/CD Git, Azure DevOps, Jenkins Database Systems SQL Server, Oracle, Snowflake (preferred) Data Modeling Dimensional modeling, Data Vault, or similar methodologies Performance Optimization Spark tuning, cluster scaling, data partitioning strategies Domain Expertise Deep understanding of Telecom Supply Chain operations, including: Device procurement and logistics Inventory and warehouse management Order fulfillment and reverse logistics Network asset lifecycle and configuration data Familiarity with ERP systems (SAP ABAP, Oracle ERP) and their integration with data platforms. Qualifications Bachelor’s or Master’s 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 Qualifications Azure 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.

  • Lead Data Engineer Telecom Supply Chain

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