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Lead data engineer

Pontypridd
Transport for Wales
Data engineer
Posted: 20h ago
Offer description

Equal Opportunities

At Transport for Wales we value diversity. It makes us stronger, helps us understand our customers better, make better decisions and be more innovative. Everyone’s different and has their own perspective so we’re building a diverse team that mirrors the communities we serve. Through this we’re determined to be one of Wales' leading inclusive employers. We’re creating an inclusive transport network that everyone in Wales can be proud of.

Who we are

At Transport for Wales, we’re on a mission to transform transport in Wales and make it fit for the future, whether that’s rail, bus, walking or cycling. We want to inspire a nation to change the way it travels, so that we all travel more sustainably and help to combat the climate emergency we’re all facing.

We’re an open and inclusive place to work, where everyone is welcome and our people are supported to reach their full potential. We want to create an environment where our people can grow and succeed. This is key to enabling us to deliver on the promises we’ve made to the people of Wales to build a sustainable transport network that meets their needs.

Role responsibilities

The Lead Data Engineer will design, build, and maintain robust, scalable, and secure data pipelines and platform that enable Transport for Wales’ (TfW) to make data-driven decisions.

1. Drive the provision of a resilient and future-ready data platform that underpins organisational growth, supports cross-functional analytics, and enables data-driven decision-making by developing and deploying scalable data pipelines leveraging a Microsoft Azure-first approach, utilising tools such as Fabric, Data Factory, Databricks, and Synapse Analytics to ensure workflows are modular, testable, and well-governed.
2. Implement robust data management practices focused on data domains, quality, and lineage by integrating data from multiple internal and external sources into a cohesive system to ensure that data is comprehensive, accurate, and traceable, supporting reliable business analysis and reporting.
3. Design, implement, and optimise physical data models that align with pipeline architecture, by using the approach that ensures efficient query performance, scalable storage, and robust integration and delivers adaptable and resource-efficient data processing, meeting the organisation’s evolving analytical and operational demands.
4. Transform raw data into meaningful insights by developing and maintaining tailored ETL (Extract, Transform, Load) processes enabling customised processes, empowering stakeholders to make informed decisions based on high-quality, processed information.

Who we’re looking for

5. Degree or MSc in Computer/Data Science or Data Engineering or equivalent experience in data engineering, data management, or a related field.
6. Proven experience in designing, building, and maintaining data pipelines using tools such as Azure Data Factory, Databricks, or Apache Spark, following modern ETL/ELT principles.
7. Experience of using programming languages such as Python, Scala and SQL and of data transformation, testing, and automation

.

8. Demonstrable knowledge of data modelling (star/snowflake schemas, dimensional models) and data warehousing within platforms such as Azure Synapse Analytics.
9. Practical experience with Microsoft Azure services, including Azure Data Lake (Gen2), Synapse, Event Hubs, and Cosmos DB, within scalable cloud-based architectures

Welsh Language Skills

The ability to speak/write Welsh would make a great addition to your application, but it is not essential for this role.

Transport for Wales supports and promotes the use of the Welsh Language by employees and will encourage them to develop, improve and maintain their Welsh Language skills. We fully support our people who want to improve their Welsh language skills, and personal development for Welsh Language skills are offered in a variety of ways such as online learning, classroom courses and funding attendance at local community courses.

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