Senior Power BI Developer

Advanced Resource Managers Ltd
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

SC Cleared Azure Data Engineer - Government client

SC Cleared Azure Data Engineer - Government client

Data Analyst, AFRS

Senior Data Engineer

Business Intelligence and Reporting Analyst

Senior Power BI Developer

Full Time

Permanent

Hybrid (1-2 days per week in London or Portsmouth offices)

£50 - 65K basic + benefits

Reporting to:Head of Data and Analytics

Are you an experienced Senior Power BI Developer looking for a new challenge?

Do you have a background in Power BI development and reporting over the last 5yrs, along with SQL, DAX + Power Query experience and ETL/ELT tools including SSIS or Azure Data Factory in an MSP environment?

Here at ARM we are recruiting for a full time permanent Senior Power BI Developer for a global IT services and consultancy client of ours.

Our client:They're a leading business with a global reach that empowers local teams, and they undertake hugely exciting work that is genuinely changing the world. Their advanced portfolio of consulting, applications, business process, cloud, and infrastructure services will allow you to achieve great things by working with brilliant colleagues, and clients, on exciting projects.

Responsible for:Designing, developing, and optimising Power BI dashboards and reports to provide business insights. Working closely with stakeholders to understand data needs, integrate data sources, and build robust BI solutions that support decision-making.

Scope:The focus of this role is to work with key business stakeholders within IT, and across the business to implement Power BI solutions and a CoE (Community of Excellence). This role will initially be focused on the processes within Finance, Lead to Cash and Hire to Retire.

Responsibilities:

  • Design, develop, and maintain interactive Power BI reports and dashboards.
  • Implement DAX (Data Analysis Expressions) for complex calculations and measures.
  • Create visually appealing, user-friendly data visualizations for business users.
  • Develop data models in Power BI using Power Query (M language).
  • Optimise data transformations, relationships, and performance tuning.
  • Connect Power BI with Azure Synapse, and APIs.
  • Write advanced SQL queries for data extraction, transformation, and aggregation.
  • Work with Stored Procedures, Views, and Query Optimisation.
  • Optimize Power BI report performance (reducing load times, improving DAX efficiency).
  • Ensure data governance, compliance, and security best practices are followed.
  • Work closely with business analysts, data engineers, and stakeholders to define reporting needs.
  • Present insights and recommendations based on Power BI dashboards.
  • Provide Power BI training and best practices to business users and junior developers.
  • Work with Power Automate and Power Apps for process automation.

Qualifications:

Essential-

  • Bachelor's Degree in Computer Science, Data Science, Information Systems, or a related field.
  • 5yrs+ of experience in Power BI development and BI reporting.
  • Practical experience of leading the set up a Centre/Community of Excellence and promoting localized self-serve reporting with Power BI.
  • Strong expertise in DAX, Power Query, and SQL.
  • Experience with ETL/ELT tools, Synapse Analytics, Azure Data Factory or SSIS.
  • Experience in building complex dashboards and performance tuning.
  • Good understanding of data modelling, governance, and security.
  • Microsoft Certified: Power BI Data Analyst Associate (PL-300).
  • Microsoft Certified: Azure Data Fundamentals (DP-900).
  • Strong problem-solving skills with attention to detail and the ability to troubleshoot complex data issues.
  • Excellent communication and collaboration skills, able to work across teams to deliver solutions that meet business needs.

Desirable:

  • Experience of working within an international IT Managed Services company.
  • Microsoft Certified: Azure Data Engineer Associate (DP-203).

Some of the benefits include:

  • Healthcare and dental insurance.
  • Company pension is matched up to 5%.
  • 25 days annual leave entitlement plus bank holidays and the option to purchase 5 extra days.
  • Life assurance - 4 x annual salary.
  • Cycle to work scheme.
  • Client prioritises internal development opportunities and offer access to our Udemy training platform with over 5000 training courses.

#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.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.