Senior BI Developer - FS Client with Data Driven Culture - REF 594

Interface Recruitment UK
Leeds
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Business Intelligence Developer

Senior Data Scientist

Group Director, Business Intelligence & Customer Master (Basé à London)

Senior Microsoft SQL Developer - Fintech SaaS. Full Remote

Senior Microsoft SQL Developer - Fintech SaaS. Full Remote

Senior Microsoft SQL Developer - Fintech SaaS. Full Remote

Vacancy Title:Business Intelligence Developer

Salary From:£30000

Salary To:£45000

Department:Finance

A rapidly expanding business that requires the establishing of a BI function to ensure that it drives consistency in reporting and data definitions across the Group as it expands, and ensure that the business is supplied with innovative, relevant and actionable reporting to support a data-driven decision making culture throughout the Group. The Senior BI Developer will support the BI Team in providing and managing high quality, timely and accurate reporting and analysis across all business functions to enable measured decision making, and support the day to day operations for continued growth of the business.

You’ll be responsible for:

  1. Day-to-day people management of BI Developers and Analysts
  2. Coaching and monitoring of developers against setting of individual objectives and goals
  3. Manage and deliver BI in line with BI Programme Manager roadmap
  4. Present technical BI solutions to non-technical stakeholders
  5. Take ownership and responsibility of the technical design, architecture and BI solution, keeping complete and end to end technical BI delivery goals in focus
  6. Provide assistance to the technical team; be able to provide technical solutions and answers to difficult and complicated business issues.
  7. ETL scripting, data modelling and report/dashboard delivery within BI tool
  8. Develop technical processes and strategy for business demands managed efficiently and effectively, giving both ad-hoc and strategic considerations to the solutions.
  9. Develop BI tool architecture including data presentation, data modelling, data blending, metadata and semantic layer development and governance
  10. Support significant data and BI tool migration projects
  11. Ensure BI reporting is governed to the highest degree in line with developed Business Glossary and Business Semantic Layer
  12. Support, promote & manage Data Warehouse roadmap delivery through detailed requirements provision and building strong relationships with data architects across the business
  13. Ensuring the hardware and software are up to date and fit for purpose for BI tool and user demands

You’ll need to evidence the following qualifications, skills and experience:

  1. Proven experience/knowledge on Microsoft stack SSIS and SSRS and SQL server
  2. Experience of producing reporting and BI through Qlikview or similar enterprise BI tools
  3. Proven experience/knowledge of building data warehouses for successful and efficient delivery of reports, KPIs and dashboards
  4. Ability to review the existing code and set up best coding practices and standards across all BI development
  5. Enhancing query and report performance
  6. Strong knowledge of relational & dimensional modelling with Kimball design
  7. Preparing technical artefacts such as (but not limited to) Data Mapping, Data Lineage, Metadata, Logical and Physical Data Models for complex data structures
  8. Good understanding of end-to-end BI development life cycle
  9. Effective communicator with good organisational, prioritising and influencing skills
  10. Advanced Microsoft office skills (Excel, Power Point, etc)
  11. People management, leadership, provoking enthusiasm and efficiency within team
  12. Promoting process adherence and compliance
  13. Able to prioritise multiple tasks and work under pressure for senior business people
  14. Ability to adapt & change reporting requirements to suit business needs
  15. Ability to work in a fast paced environment and manage / prioritise workload

The Benefits:

  1. Competitive salary with annual bonus
  2. Contributory pension
  3. 3% flexible benefits - including cycle to work, critical illness, dental insurance, childcare vouchers, travel insurance, dining club, retail discounts and the option to buy up to one week’s worth of holiday subject to start date
  4. Free shuttle bus from Leeds City Centre
  5. Subsidised on-site restaurant
  6. Free on-site gym
  7. Excellent coaching and training

Please apply quickly as the roles will go fast.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Jobs

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Jobs Careers

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Jobs

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.

🍪 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.