Power Apps Developer

London
2 months ago
Applications closed

Related Jobs

View all jobs

PowerApps Developer (Engineering, Construction)

Data Engineer

Business Intelligence Developer

Windows Application Developer (C#)

C# Developer (Windows Applications)

Data Engineer (5 Months Fixed Term Contract)

PowerApps Developer

Length: 6 months

Location: Hybrid - 3 days on site in Marble Arch

Salary: £69,000 per annum

We are actively looking to secure a PowerApps Developer to join Experis as one of our expert consultants, delivering services to our clients.

Experis Consultancy is a Global entity with a well-established team with over 1000 consultants on -assignment across 20 clients globally. Our UK operation is growing and has very aggressive plans for expansion over the coming years. We form part of the Manpower group of companies that turn over $20 billion a year collectively.

Experis UK have partnerships with major clients across the UK spanning multiple industries; our approach is a very personal one, with both our clients and our own employees. We are passionate about training, technology and career development.

Job purpose

With a real passion for using data to enable colleagues to make better data driven decisions, you create robust, yet flexible applications to help colleagues operate a more effective and customer focused business. You investigate business problems and providing targeted tooling to support the culture change required to become a data driven organisation.

Key accountabilities, responsibilities, and measures

Understands reports user requirements and can provide solutions that add value and meet business needs
Understands C&H systems and data sources and can link these to provide accurate and timely reporting
Asks stakeholders analytical question and uses excellent problem-solving skills to present potential options and solutions
Helps decision-makers, by presenting data in an accessible, informative way.
Understands the key business drivers for the business and how they relate to the overarching business strategy
Good understanding of business functions and the financial and operational process drivers of the business to inform risks, opportunities and priorities
Collects, organises and manipulates large amounts of data using databases and other technologies.
Presents and re-structure data tailored to required output ensuring that all reporting meets user requirements and look for ways to continually improve accuracy and usability
Works with large datasets using frameworks such as Azure Data Lake Services, Databricks and Azure Synapse. Understands how to access and join data from different databases.
Manage business incidents, driving data quality and source system issues to successful conclusions and maintaining the ongoing quality of analytical assets
Builds data models and uses insight to make recommendations
Participates in the effective prioritisation and management of team workload and backlog, as well as proactively identifying new opportunities.Key skills

Can tell a story through data
Thinks creatively about problems and can support decision makers' business-related questions using available data
Reviews, refines and validates user requirements in detail, to design the scope needed to land effective data led change
Great stakeholder management and user engagement to build an audience and drive adoption.
Excellent problem solver
Good understanding of business functions and the financial and operational process drivers of the business
Experience using visualisation tools e.g. Power BI, Spotfire, Tableau
Experience querying data query using SQL or Python
Excellent ability to trans

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.