VodafoneThree - Data Engineer

In this role you will design, build, and maintain scalable data pipelines and platforms to power advanced analytics and AI-driven decision making at VodafoneThree. You will collaborate with Data Engineers, Data Scientists, and DevOps colleagues to ensure data is reliable, secure, and accessible for personalised customer experiences. You’ll contribute to the Unified Data Platform and support AI-enabled data engineering initiatives. This is a chance to work on data solutions that scale across the UK and help close the digital divide while joining a collaborative, inclusive team that values real-world impact. You will thrive in a fast-paced, cross-functional environment and help shape the next‑

• great pay
• bonuses
• up to 28 days off plus bank holidays
• paid time for charity work
• pension plan
• learning tools

• Design, build, and maintain robust, scalable data ingestion pipelines aligned with engineering best practices
• Collaborate with Data Engineers, Data Scientists, DataOps, and DevOps to ensure data availability and quality
• Assess and improve data quality, proactively addressing issues to maintain trusted datasets
• Develop and optimise large-scale data processing solutions handling significant data volumes securely
• Create and maintain clear documentation with defensive programming and continuous improvement
• Contribute to agile delivery, own sprint commitments, and support teammates to achieve goals
• Partner with stakeholders to deliver solutions for strategic initiatives, customer insights, and marketing
• Support evolution of the Unified Data Platform and adoption of Agentic AI frameworks

• Experience assessing and improving data quality using SQL and/or Python
• Ability to develop scalable data pipelines with Spark, PySpark, Hive, and BigQuery
• Extensive experience with large codebases using GitHub, GitLab, Gitflow, EnvFlow, or similar
• Comfort with development environments and CLI tools (e.g., PyCharm, VS Code, Bash, Zsh)
• Hands-on use of notebook technologies (Jupyter, Zeppelin, Google Datalab) for analysis
• Experience with cloud-based Big Data platforms (AWS and/or GCP)
• Ability to thrive in agile environments (Scrum, Kanban or similar)
• Understanding of software and data lifecycle management

• collaborative
• problem-solving
• continuous learning
• SQL
• Python
• Spark