Data Warehouse Manager - Fabric Lakehouse, PySpark

TXP
West Bromwich
1 month ago
Applications closed

Related Jobs

View all jobs

Data Warehouse Manager

Data Science / Data Mining Specialist

Data Scientist - London, UK (Fully REMOTE)

Data Analyst

Systems and Data Analyst

Business Intelligence and Database Lead

Data Warehouse Development Manager

Duration: 9 months

£580 Per Day - Inside IR35

Location: 2-3 days per month in the West Midlands, the rest can be remote working

The Data Warehouse Development Manager will lead the design, development, and implementation of an enterprise-wide data warehouse using Microsoft Fabric, consolidating data from multiple ERP systems and applications across our client's acquired businesses.

This role requires a blend of technical expertise, leadership capability, and strategic thinking to deliver a solution that meets our global client's complex reporting and analytics needs.

Our client is looking for experience of working on a Fabric Lakehouse project - someone who has completed a Lakehouse with PySpark project rather than part way through.

The following is essential -

Strong technical and development management skills.
Strong experience in designing and building enterprise data warehouses or data platforms in a leadership role.
Completed a Lakehouse with PySpark project.
Hands-on expertise in the development of a data Lakehouse within the Microsoft Fabric or Databricks data platforms.
Significant experience with PySpark and Spark-based data processing.
Deep understanding of data warehouse design principles, Lakehouse architectures.If your profile demonstrates strong and recent experience in the above areas - please submit your application ASAP to Jackie Dean at TXP for considera...

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.

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

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.