At a Glance
- Tasks: Own the analytics process from data quality to delivering polished dashboards for senior stakeholders.
- Company: Join a leading PE-backed fintech organisation focused on modern analytics.
- Benefits: Enjoy remote work flexibility, competitive pay, and opportunities for career growth.
- Other info: High visibility role with potential for long-term opportunities.
- Why this job: Make a real impact with your analytics skills in a dynamic, tech-driven environment.
- Qualifications: Experience with dbt, Snowflake, and strong dashboard development skills required.
The predicted salary is between 56700 - 69300 £ per year.
- Senior Analytics Engineer – PE Backed Financial Technology Organisation
- Predominantly remote | Occasional London attendance
We are supporting a leading PE backed financial technology and data-led organisation that is investing significantly in its modern analytics capability.
The organisation is looking for an experienced Analytics Engineer who can take genuine end-to-end ownership from understanding complex source data and resolving quality issues through to building robust data models and delivering polished reporting products for senior stakeholders.
This is a highly visible position offering significant autonomy.
It would suit someone who combines strong analytics-engineering fundamentals with excellent dashboard-development and stakeholder-management skills.
Key responsibilities
- Work directly with senior business stakeholders to understand reporting and analytical requirements.
- Investigate underlying data and resolve quality, consistency and reconciliation issues.
- Build and maintain reliable production data models using dbt and Snowflake.
- Design dimensional models with clearly defined facts, dimensions, grain, relationships and business metrics.
- Develop governed semantic and reporting layers that support consistent decision-making.
- Build accurate, intuitive and visually polished dashboards and reporting products.
- Own delivery from initial requirement gathering through to the finished product.
- Use AI-assisted engineering tools such as Claude Code, Codex or Git Hub Copilot to improve delivery speed and quality.
- Document models, definitions, testing and data lineage clearly.
- Required experience
- Strong hands-on production experience with dbt and Snowflake.
- Advanced SQL and a strong understanding of data quality, testing and reconciliation.
- Proven experience designing dimensional models and analytical data products.
- Strong dashboard-development experience with Power BI, Tableau, Looker, Sigma or a comparable platform.
- Evidence of personally delivering analytics products from source data through to senior-stakeholder reporting.
- Confidence working directly with senior, non-technical business stakeholders.
- Experience producing dashboards that are both technically accurate and visually strong.
- Availability to begin a new assignment at short notice.
- Experience within fintech, financial services, investment management or another data-intensive regulated environment.
- Exposure to complex financial, commercial, customer or performance data.
- Experience with Sigma Computing.
- Practical use of Claude Code, Codex, Git Hub Copilot or similar AI-assisted development tools.
- Experience working independently in an interim or consulting environment.
This is an opportunity to join a high-calibre, technology-led environment and deliver visible analytics products used by senior decision-makers.
The initial engagement is for six months, with strong potential for extension or a longer-term opportunity.
Applicants must have the right to work in the UK and be able to attend occasional meetings in London.
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Senior Analytics Engineer employer: Siena Partnership
Siena Partnership is an exceptional employer, offering a dynamic work environment where innovation and collaboration thrive. As a VP of Analytics Engineering, you will have the opportunity to lead a talented team, shape cutting-edge data solutions, and drive impactful change within the organisation. With a strong focus on employee growth and a culture that values strategic thinking and technical excellence, Siena Partnership is committed to fostering your professional development while making a meaningful impact in the analytics space.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Analytics Engineer
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We think you need these skills to ace Senior Analytics Engineer
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Siena Partnership, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Siena Partnership, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Siena Partnership’s attention and show the tangible impact of your work.
How to prepare for a job interview at Siena Partnership
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Siena Partnership.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Siena Partnership.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Siena Partnership.
