Senior Microsoft SQL Developer - Fintech SaaS. Full Remote

Birmingham
9 months ago
Applications closed

Related Jobs

View all jobs

(Senior) Forecasting Data Engineer

(Senior) Forecasting Data Engineer

Business Intelligence Development Manager

Senior Business Intelligence Developer

Senior Data Engineer - Platforms and Tooling

Senior Data Engineer - Platforms and Tooling

This is a fantastic opportunity to join a ground-breaking Fintech SaaS company re-defining the way that financial advisers, platforms and private wealth managers report, communicate, and exchange data with their clients.
Ready to advance your career and join an industry leader with a constant mission to innovate?
Role Info:
Senior Microsoft SQL Developer
100% UK Remote
Up to £70,000
Plus Incredible Benefits Package including Life Assurance, Private Health Cover, Pension Scheme, and More…
Values: Innovative, Flexible, Responsive, Professional, Integrity
Product / Service: Fintech SaaS – Leading supplier of investment workflow and data distribution services to the UK financial advisory market. Our software integrates with most of the leading investment platforms and back-office systems in the UK.
Your Skills / Background: Design and Build of High Volume Database Architectures, TSQL, SQL, Performance Tuning.
Who we are:
We’re Sprint Enterprise Technology – a small, high-impact fintech company, doing big things in the UK wealth management industry, and we have the awards to prove it! Our mission is to bring about a more open and integrated wealth management industry by enabling the flow of rich and accurate data between systems.
We operate in a fast-paced, customer-first environment that embraces innovation. Our technology stack is Microsoft-based, running on a VMware virtualized private cloud, carefully managed by our own Infrastructure Engineers and our hosting partners. We run a network of SQL Servers, ensuring high availability and performance for our data-driven solutions.
Our product FINIO is the award winning data hub that connects investment platforms, discretionary fund managers with software providers and advisory firms for the flow of investment data. It helps the wealth management sector become more efficient, integrated and enables the flow of complex investment data that is increasingly required to power today’s software systems.
The Senior Microsoft SQL Developer role:
We are seeking an experienced Senior Microsoft SQL Developer to work closely alongside our Chief Data Architect (ex Microsoft) and Head of Development to maintain and develop our current and future data centric financial technology solutions.
This is a fully remote opportunity within the fintech sector.
About you:
• An expert in the design and build of high performance / high volume database architectures
• Highly proficient in TSQL including Stored Procedures, Views, Triggers, and UDF's
• Have in-depth knowledge of SQL Internal Architecture (Metadata, Indexes, Statistics etc.)
• Skilful in performance tuning (using all available tools / techniques), refactoring existing SQL, monitoring high availability clusters and patching live systems
• Experienced in SQL CLRs, SSRS, and Power BI
• As a key member of the team in a growing business, you must be a natural communicator
Additional useful skills and experience:
• SQL CLR's
• SSRS
• Power BI/SQL Reporting
• Power BI / on premise SSAS integration
• Experience of hybrid / full migration from on premise SQL to Azure
Why you’ll love this role:
• Work in a fully remote, highly collaborative environment in the fintech space
• Be part of a fast-moving, startup-style culture that values creativity and impact
• Engage directly with customers, making a real impact on their experience and satisfaction
• Enjoy a diverse, dynamic, and supportive work culture where your contributions make a real difference
What’s on Offer:
• Work from home (with funded meet ups from time to time)
• Flexible working (where practical)
• 25 days holiday (plus bank holidays) plus ½ day for each year's service (to max 30 days)
• 2 days corporate social responsibility leave
• Holiday purchase scheme (buy/sell up to 5 days)
• Life Assurance (4 x salary)
• Contribution to Private Health Cover
• Subscription to a Wellbeing service and Employee Assistance Programme
• Contributory Pension Scheme via Salary Sacrifice
• Salary Sacrifice for additional qualifying benefits (e.g. extra pension contributions, EV purchase)
Interested? Apply here for a fast-track path to our Leadership Team.
Application notice... We take your privacy seriously. As you might expect you may be contacted by email, text or telephone. Your data is processed by our talent partner RR (Recruitment Revolution) on the basis of their legitimate interests in fulfilling the recruitment process. Please refer to their Data Privacy Policy & Notice on their website for further details

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers Jobs

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

Jobs

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Education Jobs

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.