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Sword is a leading provider of business technology solutions within the Energy, Public and Finance Sectors, dedicated to driving transformational change for our clients. We leverage proven technology, specialist teams, and extensive domain expertise to create robust technical foundations across platforms, data, and business applications. Our mission is fueled by a passion for technology as a means to solve complex business problems and achieve our clients' objectives.
About The Role
This Data Engineer role offers an excellent opportunity for someone with a good understanding and working knowledge of designing and building robust data pipelines, integrating complex data sources, and developing solutions using Azure Data Services, Microsoft Fabric, Power BI, and Purview.
As an experienced Data Engineer, you will:
- Handle more advanced engineering tasks
- Drive improvements to existing pipelines
- Contribute to the design of scalable, high quality data architectures
- Collaborate directly with clients and cross-functional teams
- Translate real business needs into effective data solutions
- Begin to support and mentor junior engineers
This role is ideal for someone who wants to grow toward senior-level responsibilities, gain exposure to architectural thinking, and work with cutting-edge technologies, including Microsoft Foundry as part of emerging AI-driven capabilities. Candidates should apply if they're looking for a role that blends hands-on engineering, problem-solving, continuous learning, and meaningful contribution to client outcomes within a high-performing Data & AI business unit.
A Data Engineer Is Responsible For Several Key Activities
- Design, build, and maintain scalable, secure, and high performing data pipelines using Azure Data Factory, Synapse, Fabric Pipelines, or Databricks
- Integrate data from multiple systems into Azure Data Lake Storage or OneLake, ensuring consistency, reliability, and performance
- Develop and maintain ELT/ETL processes using Azure-native tools and Fabric capabilities, optimising for cost and performance
- Build and maintain Microsoft Fabric artefacts including lakehouses, warehouses, notebooks, dataflows, and semantic models
- Perform advanced data transformations using SQL, Python, Spark, or Fabric Data Engineering experiences to prepare data for analytics and reporting
- Manage and optimise data models used by Power BI, ensuring good performance, relationships, quality, and reusability
- Support enterprise BI development by preparing datasets, semantic models, and reusable components within Power BI and Fabric
- Apply data governance and security best practices by implementing Purview classification, lineage, access controls, and policies
- Conduct data quality checks, data validation routines, and issue resolution to ensure trustworthy and reliable datasets
- Work closely with cross-functional teams (data architects, analysts, data scientists, product teams) to understand requirements and translate them into robust data solutions
- Engage directly with clients and stakeholders to clarify data needs, communicate progress, and explain technical concepts in a clear, accessible way
- Take ownership of more complex engineering tasks and assist senior engineers with solution components requiring deeper technical insight
- Mentor junior engineers by providing guidance, performing code reviews, and sharing best practices in engineering standards and Azure environments
- Contribute to CI/CD processes, version control practices, and automated deployment pipelines for data solutions
- Support the creation of documentation for pipelines, datasets, data models, and solution designs
- Troubleshoot pipeline failures, performance issues, and data inconsistencies, ensuring the stability and reliability of production workloads
- Stay current with emerging tools and capabilities across Azure, Microsoft Fabric, Power BI, Purview, and Microsoft Foundry
- Identify opportunities to improve efficiency, automation, scalability, or maintainability across existing pipelines and solutions
- Contribute to internal knowledge sharing, best-practice development, and engineering accelerators or templates
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Requirements
- Deep understanding of Azure Data Factory, Synapse, Fabric, Power BI and Databricks
- Experience in Fabric/data architecture
- Experience in Fabric/data migrations
- Understanding of the requirements of stringent data governance
- Ability to consult with clients
- Proven experience of mentoring teams
- Experience of advanced data transformations using SQL, Python, Spark, or Fabric Data Engineering experiences to prepare data for analytics and reporting


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Benefits
At Sword, our core values and culture are based on caring about our people, investing in training and career development, and building inclusive teams where we are all encouraged to contribute to achieve success. We offer comprehensive benefits designed to support your professional development and enhance your overall quality of life. In addition to a Competitive Salary, here's what you can expect as part of our benefits package:
- Personalised Career Development: We create a development plan customised to your goals and aspirations, with a range of learning and development opportunities within a culture that encourages growth.
- Flexible working: Flexible work arrangements to support your work-life balance. We can't promise to always be able to meet every request, however, are keen to discuss your individual preferences to make it work where we can.
- A Fantastic Benefits Package: This includes generous annual leave allowance, enhanced family friendly benefits, pension scheme, access to private health, well-being, and insurance schemes.
At Sword we are dedicated to fostering a diverse and inclusive workplace and are proud to be an equal opportunities employer, ensuring that all applicants receive fair and equal consideration for employment, regardless of whether they meet every requirement. If you don't tick all the boxes but feel you have some of the relevant skills and experience we're looking for, please do consider applying and highlight your transferable skills and experience. We embrace diversity in all its forms, valuing individuals regardless of age, disability, gender identity or reassignment, marital or civil partner status, pregnancy or maternity status, race, colour, nationality, ethnic or national origin, religion or belief, sex, or sexual orientation. Your perspective and potential are important to us.
If we can do anything to help make the hiring process more accessible, please let our talent acquisition team know when you apply so we can support any adjustments.
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