Assistant Manager_GCP Data Engineer...

We are looking for a skilled Big Data Engineer to design, build, and manage data ingestion and processing applications on Google Cloud Platform. This role involves extensive work with Google Cloud services such as BigQuery, Dataflow, Composer, Cloud Storage, and Dataproc, with a focus on ensuring optimal performance and scalability. You will also contribute to developing real-time data processing systems, containerization strategies, and implementing modern DevOps practices to support machine learning applications and MLOps industrialization.

Responsibilities include designing, building, and managing Big Data ingestion and processing applications on Google Cloud using BigQuery, Dataflow, Composer, Cloud Storage, and Dataproc. You will optimize performance and analyze distributed computing tools like Spark and Apache Beam (Dataflow). The role also involves developing cloud-optimized solutions for machine learning applications, building real-time data processing systems using Kafka, Pub/Sub, Spark Streaming, or similar technologies, and managing the development lifecycle for agile software projects. You will be responsible for converting proof-of-concept machine learning models into production-ready solutions (MLOps), delivering customer-oriented solutions efficiently and collaboratively, proactively planning and managing project dependencies, and implementing robust solutions in test and production environments.

Ideal candidates will possess a Professional Google Cloud Data Engineer certification, strong analytical and technical skills for impact analysis and root cause identification, and excellent communication abilities for engaging with diverse stakeholders. A solid understanding of the Big Data and Data Science ecosystems is required, along with 3-5 years of relevant work experience. Experience in building and deploying containers using Swarm/Kubernetes, knowledge of container concepts (creating lean, secure images), and familiarity with modern DevOps pipelines are essential. Experience with streaming data pipelines using Kafka or Pub/Sub is mandatory, with a preference for Kafka experience. Telecommunications industry experience and exposure to CI/CD tools (Jenkins, Git, Jira, Confluence) are desirable. A graduate or postgraduate degree in a technical stream, preferably Engineering, is also preferred.

At Vodafone, we foster an inclusive workplace. If your experience doesn't perfectly match every requirement but you're enthusiastic about this role, we encourage you to apply. Your unique skills might be the perfect fit for this or another opportunity.

This role offers the opportunity to work with cutting-edge Big Data and cloud technologies, gain exposure to real-time data processing and machine learning applications, and thrive in a collaborative global team environment. You will benefit from career growth opportunities, continuous learning, and certification support.

Skills you will learn include advanced Google Cloud Platform services and optimization techniques, MLOps practices for scalable machine learning model deployment, real-time data streaming technologies like Kafka and Pub/Sub, containerization and orchestration using Kubernetes, and modern DevOps and CI/CD pipeline management.

Vodafone is committed to equal opportunities, celebrating diversity in all its forms. We do not tolerate any form of discrimination. Join us in building a better future—a more connected, inclusive, and sustainable world, where technology and human spirit empower us all. We challenge, innovate, and connect people and businesses globally. Our drive to delight customers fuels our experimentation, rapid learning, and collective success. Be yourself, belong, share inspiration, embrace opportunities, thrive, and make a difference.

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