Data Engineering Consultant (multiple levels)

Xcede
Birmingham, England
11 months ago
Applications closed

Related Jobs

View all jobs

Data Consultant

Ncounter Latchmere, London, TW10 5HW, United Kingdom
£80,000 – £85,000 pa

Data Consultant (SC Cleared)

Syntax Consultancy Corsham, Wiltshire, SN13 0HB, United Kingdom
£450 pd

Data Platform Solutions Architect (Professional Services)

Databricks London, United Kingdom
£40,000 – £80,000 pa Hybrid

Data Platform Solutions Architect (Professional Services) - Emerging Enterprise & DNB

Databricks London, United Kingdom

Resident Solutions Architect (Professional Services)

Databricks London, United Kingdom

Data Engineer / Consultant

Change-IT Public Sector Broad Street, Greater London, City And County Of the City Of London, United Kingdom
£60,000 – £100,000 pa
Posted
4 Jun 2025 (11 months ago)

Data Engineering Consultant (Azure) – hiring at multiple levels

Hiring in London, Midlands, Edinburgh & Glasgow

Salary Ranges from £40,000 - £65,000 + Car Allowance + Bonus

Hybrid Working (x3 days in office, x2 remote)



OVERVIEW


A major global consultancy operating across a breadth of industries & sectors is scaling it's Data function and hiring for multiple Data Engineering Consultants across various levels (Consultant, Senior & Principal). You will be joining a Data function working across a breadth of interesting projects for their clients, demonstrating both technical ability and stakeholder engagement skills when delivering impactful Data Engineering projects. Your responsibilities as a Data Engineering Consultant will include but not be limited to:


  • Leverage your technical expertise in Data Engineering to deliver impactful projects for a range of clients across their portfolio.
  • Demonstrate your knowledge of Python & Azure to deliver on engagements for major clients.
  • Collaborate effectively within a team of other Data Engineering Consultants on a breadth of projects.
  • Effectively engage and communicate with non-technical stakeholders in a role that requires both technical ability and business-facing skills.



YOUR SKILLS & EXPERIENCE


A successful Data Engineering Consultant will have the following:


  • Solid technical ability inPython,SQL&Azure(essential).
  • Strong proficiency in Microsoft Azure and relevant tools/ technologies (Databricks, Azure Data Factory, Azure Data Lake, Azure Synapse).
  • Proven understanding of DevOps best practices:CI/CD(Azure DevOps is preferred).
  • Solid communication skills and business-facing/ stakeholder engagement experience.



THE BENEFITS:


  • Competitive Salary
  • Bonus
  • Cash Car Allowance (paid out same as base salary - £4,000)
  • Hybrid Working (3 days in office, 2 from home)


HOW TO APPLY


Please register your interest by clicking the Apply Link or send your CV to


** There is no sponsorship available for this role. **

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.