At a Glance
- Tasks: Design and build scalable data pipelines to transform and deliver data from various sources.
- Company: Join a forward-thinking financial services client in South Wales.
- Benefits: Enjoy competitive salary, hybrid working, private healthcare, and generous leave.
- Other info: Be part of a small, dynamic team with excellent growth opportunities.
- Why this job: Make a real impact by transforming data processes and enabling self-service analytics.
- Qualifications: Experience in data engineering, SQL, ETL, and data modelling techniques required.
The predicted salary is between 50000 - 65000 £ per year.
IntaPeople are seeking an experienced Data Engineer to join one of their financial services focussed clients based in South Wales. This role is critical to transforming a reporting-led organisation into a proactive, insight-driven business. The Data Engineer will be responsible for developing robust data engineering solutions that reduce manual processes, improve data quality, and enable self-service analytics at scale.
You will have strong experience in data architecture, ETL development, and modern data warehousing practices, including the application of Kimball methodology and dimensional modelling, alongside a proven track record of building reliable, high-performance data solutions in a business-focused environment. This is a newly created role within the Data Engineering function due to growth and forward planning. You will join a small Data/BI team of 3-4 so being a Senior within the team will allow a large amount of responsibility and report directly into the Head of Data Engineering.
Technical Skills (at a glance)
- Proven experience in a Data Engineer or Senior Data Engineer role, delivering scalable data solutions in a business environment.
- Strong experience with SQL and transformation logic in a data warehousing environment.
- Experience designing and maintaining ETL pipelines and data integration processes.
- Strong experience of Kimball data modelling techniques (e.g. star schema, dimensional modelling).
- Experience working within a Microsoft data stack (e.g. SQL Server, Azure Data Factory, Azure Synapse, Microsoft Fabric, or similar).
- Experience working with structured data from multiple operational systems.
- Strong understanding of data quality, governance, and best practices for managing trusted data assets.
- Experience working closely with BI/analytics teams to support reporting and insight delivery.
- Strong problem-solving skills with the ability to diagnose and resolve data issues quickly and effectively.
Key Responsibilities (but not limited to)
- Design, build, and maintain scalable, robust data pipelines to ingest, transform, and deliver data from multiple source systems.
- Develop and optimise the enterprise data warehouse to provide a single, trusted source of data across the organisation.
- Reduce reliance on manual data processing by automating data flows, integrations, and transformations.
- Ensure data is accurate, consistent, and reliable through the implementation of data quality checks, monitoring, and validation processes.
- Work closely with BI, analytics, and business stakeholders to understand data requirements and enable high-quality reporting and insight.
- Support the transition to self-service analytics by ensuring data is structured, accessible, and well-governed.
- Design efficient, scalable data models that support both operational reporting and advanced analytics use cases.
- Improve performance, scalability, and cost-efficiency of data processes and infrastructure.
- Integrate new data sources (e.g. operational systems, third-party platforms) into the data platform in a consistent and governed manner.
- Establish and maintain best practices in data engineering, including documentation, version control, testing, and deployment processes.
- Collaborate with Technology and BI teams to align data architecture with overall system architecture and business strategy.
- Stay up to date with emerging data engineering tools, technologies, and best practices to continuously enhance the data capability.
Role overview at a glance
- Competitive Salary depending on experience – please enquire for more information.
- Starting on 25 days annual leave per year.
- Hybrid working – 2-3 days onsite - Newport.
- Free parking on-site.
- Bonus Scheme based on performance.
- Private Medical Healthcare.
- Group Life Insurance (4x basic annual salary).
- Employee Assistance Programme.
- Cycle to Work Scheme.
- Enhanced Maternity & Paternity Benefits.
- Performance and Development Framework.
- Long service awards.
This role is a hybrid role with a 2-3 days office requirement for collaboration, workshops and stakeholder meetings per week on-site in the Cardiff/Newport area (South Wales).
Interviews will be held w/c 13th and 20th July onwards due to annual leave and availability.
Please note we cannot provide sponsorship to candidates who are not eligible to live and work within the UK without restriction.
For more information please call Nathan Handley on (phone number removed) or click APPLY now for immediate consideration.
Senior Data Engineer in Newport employer: IntaPeople
Join a forward-thinking financial services company in South Wales as a Senior Data Engineer, where you'll play a pivotal role in transforming data processes and driving insights. With a strong emphasis on employee growth, the company offers a competitive salary, hybrid working arrangements, and a comprehensive benefits package including private medical healthcare and enhanced parental leave. The collaborative work culture fosters innovation and allows you to make a significant impact within a small, dedicated team.
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We think this is how you could land Senior Data Engineer in Newport
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We think you need these skills to ace Senior Data Engineer in Newport
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
