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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.
Reference : Lead Data Engineer – Telecom Supply Chain jobs

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Published at 07-12-2025
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