Big Data Engineer

Job Description Roles & Responsibilities Join Us At Vodafone, we re not just shaping the future of connectivity for our customers we re shaping the future for everyone who joins our team. When you work with us, you re part of a global mission to connect people, solve complex challenges, and create a sustainable and more inclusive world. If you want to grow your career whilst finding the perfect balance between work and life, Vodafone offers the opportunities to help you belong and make a real impact. Role Purpose You are building the foundation that our entire software and AI stack relies on. You won't be doing basic drag-and-drop data integration you will write distributed backend code to process large-scale batch and real-time data streams Role Responsibilitoes Distributed Big Data Processing: Write, optimize, and debug large-scale batch data transformation jobs using Apache Spark . Real-Time Event Streaming: Implement and maintain event-driven streaming pipelines using Apache Kafka to deliver low-latency data across microservices. ETL/ELT Orchestration: Build automated ingestion pipelines using orchestrators (example : Airflow or any tool) and data transformation layers to pull from APIs and databases. Lakehouse Governance: Structure and manage our Data Lakehouse , organizing schemas, enforcing data quality rules, and optimizing query performance for downstream BI and AI teams. Competencies and Qualifications Advanced SQL: Write complex window functions and Common Table Expressions (CTEs); analyze and optimize query execution plans for speed. Backend Programming: Strong coding proficiency in Python (for scripting/orchestration) OR Scala/Java (for high-performance Spark/Kafka engineering). Distributed Systems (Spark/Kafka): Solid understanding of how distributed compute works specifically Apache Spark (handling data skew, transformations vs. actions) and Apache Kafka (brokers, topics, partitioning, offsets). Lakehouse Architectures: Foundational knowledge of open table formats like Apache Iceberg , or Delta Lake , and how to model data across Bronze, Silver, and Gold storage layers. Infrastructure: comfortable with basic Linux admin & bash commands, monitoring and automation for data services. Not a perfect fit? Worried that you don t meet all the desired criteria exactly? At Vodafone we are passionate about empowering people and creating a workplace where everyone can thrive, whatever their personal or professional background. If you re excited about this role but your experience doesn t align exactly with every part of the job description, we encourage you to still apply as you may be the right candidate for this role or another opportunity. Who we are We are a leading international Telco, serving millions of customers. At Vodafone, we believe that connectivity is a force for good. If we use it for the things that really matter, it can improve people's lives and the world around us. Through our technology we empower people, connecting everyone regardless of who they are or where they live and we protect the planet, whilst helping our customers do the same. Belonging at Vodafone isn't a concept; it's lived, breathed, and cultivated through everything we do. You'll be part of a global and diverse community, with many different minds, abilities, backgrounds and cultures. ;We're committed to increase diversity, ensure equal representation, and make Vodafone a place everyone feels safe, valued and included. If you require any reasonable adjustments or have an accessibility request as part of your recruitment journey, for example, extended time or breaks in between online assessments, please refer to https://careers.vodafone.com/application-adjustments/ for guidance. Together we can. Desired Candidate Profile Advanced SQL: Write complex window functions and Common Table Expressions (CTEs); analyze and optimize query execution plans for speed. Backend Programming: Strong coding proficiency in Python (for scripting/orchestration) OR Scala/Java (for high-performance Spark/Kafka engineering). Distributed Systems (Spark/Kafka): Solid understanding of how distributed compute works specifically Apache Spark (handling data skew, transformations vs. actions) and Apache Kafka (brokers, topics, partitioning, offsets). Lakehouse Architectures: Foundational knowledge of open table formats like Apache Iceberg , or Delta Lake , and how to model data across Bronze, Silver, and Gold storage layers. Infrastructure: comfortable with basic Linux admin & bash commands, monitoring and automation for data services. Company Industry TelecomISP Department / Functional Area IT Software Keywords Big Data Engineer Get real-time job updates only on our App