Project Manager - Data Analytics/ Power BI - Birmingham

Birmingham
9 months ago
Applications closed

Related Jobs

View all jobs

Project Manager - Data Strategy Implemen, Fixed Term

Data Engineer

Data Analyst

Data Analyst Placement Programme

Data Analyst Placement Programme

Business Intelligence Consultant - Power BI & SQL

Data and Analytics Project Manager - PowerBI/Devops - Birmingham/Remote

Inside IR35

£650-£675

1-2 days per month on-site (Minimum)

Our customer is currently seeking a skilled Project Manager with a strong background managing complex Data & Analytics projects. Joining a well-established delivery team, you'll play a key role in managing multiple high-impact and strategically important projects, working closely with the Programme Manager to ensure smooth execution and alignment with business objectives.

The most suitable candidate would have extensive Data & Analytics project experience as well as Finance, Data Warehouse and Power BI.

Key responsibilities:

End-to-end project management across planning, delivery, and evaluation phases
Coordination of cross-functional teams and third-party suppliers for seamless project execution
Expertise in project scheduling tools (e.g. Microsoft Project), with strong milestone and dependency tracking
Risk and issue management, including proactive mitigation and resolution strategies
Strong collaboration with stakeholders, IT, and vendors to deliver scalable, fit-for-purpose solutions
Regular reporting on project progress, budgets, and performance metrics to ensure transparency
Leadership of data-driven projects aligned to firm-wide Data & Analytics strategy
Strong relationship-building skills across business units and client teams
Support for implementation and adoption of new data tools and reporting solutions
Application of best-practice project management methodologies and IT standards - experience moving towards Agile ways of working

Desirable skills -

Proven ability to collaborate effectively with third-party vendors and large-scale outsourcing partners
Background in delivering projects within professional services environments, particularly in the legal sector
Demonstrated experience in implementing solutions using the Power BI platform
Familiarity with DevOps practices and the sprint-to-release development lifecycle

Interested? Please submit your updated CV to Olivia Yafai at Crimson for immediate consideration.

Not interested? Do you know someone who might be a perfect fit for this role? Refer a friend and earn £250 worth of vouchers!

Crimson is acting as an employment agency regarding this vacancy

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.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.