Business Intelligence Manager

Meon Vale
2 weeks ago
Applications closed

Related Jobs

View all jobs

Business Intelligence & Performance Manager

Business Development Manager

HR Business Intelligence Analyst

Business Intelligence Engineer

HR Business Intelligence Analyst

Business Analyst - Assistant Manager

We are looking for a highly motivated Business Intelligence Manager to join our dynamic team. You will oversee the delivery and management of a robust scalable business intelligence platform and its supporting systems to ensure that they meet the business goals of the organisation. Defining how the data will be stored, accessed, consumed, integrated, and managed by different data entities and IT systems, as well as any applications using or processing that data in some way.
As part of our core values, Unimetals offers an inclusive and dynamic environment and we welcome people from a variety of different backgrounds.
Your Key Responsibilities

  • Lead the architecture, design, and development of the business intelligence platform whilst implementing/maintaining compliance with the business intelligence and analytics strategy
  • Responsible for the training, coordination and evaluation of cross-departmental business analysts and business partners
  • Collaborate with key stakeholders to select appropriate platforms and services to support the business intelligence strategy
  • Interpret and co-ordinate the organisation’s data needs whilst making sure that they are designed in accordance with the appropriate data architectures and strategy
  • Define and manage the technical principles, vision, and standards for the data warehouse/data lake ensuring the design can scale to handle additional data and business demands
  • Manage and monitor the work of vendor partner resources and the Database Administrator
  • Maintain knowledge of external and internal data capabilities and trends, facilitating the evaluation of vendors and products including topic-specific deep dives to address business urgencies
  • Establish and manage governance protocols to support the business intelligence strategy
  • Continually review and monitor the integrity, security and service continuity of data systems and their dependencies
  • Hands-on management of datasets, lifecycles, access security and policies
  • Create documentation and presentations, lead discussions with business and technology owners
  • Liaise with the Network Manager to ensure Disaster Recovery requirements can be met including any assigned recovery time and recovery point objectives
  • Perform such other duties as the Company may from time to time reasonably require
  • Comply with all Company policies related to Code of Conduct, Environmental, Health and Safety and Community
    About You (Key Skills/Competencies)
  • Minimum of 5 years of working experience in a data related role
  • Proficiency in SQL with familiarity of associated data modeling tools
  • Deep understanding of data management fundamentals and data storage principles
  • Understanding of systems architecture and ability to design scalable, robust systems
  • Comprehensive understanding of distributed computing environment concepts
  • Competency with Microsoft development tools and technologies
  • Knowledge of data security and privacy practices
  • Knowledge of cloud computing and experience with platforms like Amazon Web Services (AWS) or Microsoft Azure beneficial
  • Strong analytical and problem-solving abilities
  • Ability to communicate effectively with both technical and non-technical stakeholders

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.

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.

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.

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.