Remote Azure Data Engineer (Contract)

Discovered MENA
Leigh
11 months ago
Applications closed

Related Jobs

View all jobs

Urgent | Contract Senior Data Engineer - Azure + Databricks + Snowflake

Lead Data Scientist - Remote

Lead Data Scientist - Remote

Data Scientist

Data Analyst

Data Warehouse Engineer - 6 Month FTC

Title:

Azure Data Engineer
Location:

Fully remote (working UAE hours)
Salary:

5k GBP per month

Are you the right candidate for this opportunity Make sure to read the full description below.

Are you a data expert with a passion for building scalable, cloud-first data pipelines? We’re hiring an experienced

Azure Data Engineer

to join a fast-growing team focused on developing a centralised, enterprise-grade data warehouse in the Azure cloud.

This is a

full-time remote role

open to candidates located within

GMT +1 to +6 time zones . If you thrive in fast-paced environments, take extreme ownership of your work, and want to make a real impact in a data-driven organization - this could be the perfect opportunity for you.

What You’ll Be Doing:
Designing, building, and optimizing data models for a modern data warehouse on Azure
Creating and maintaining secure, scalable data pipelines and ingestion workflows
Leveraging

Azure Synapse Analytics

and

ADF

to deliver robust ELT solutions
Ensuring pipeline execution, availability, and reliability across platforms
Owning physical data models and collaborating with BI teams on reporting layers
Supporting data discovery, KPI definition, and data quality initiatives
Documenting architecture, metadata, and data lineage for project transparency
Driving performance optimization and issue resolution across the data stack

What We’re Looking For:
5+ years of experience in data engineering, integration, and ETL/ELT projects
3+ years hands-on with Azure tools
Strong command of

SQL , stored procedures, and data modeling (Kimball or 3NF)
Solid understanding of data warehouse architecture and best practices=

Bonus Skills:
Familiarity with Salesforce (SFDC Sales Cloud), Google Analytics, or Airtable
Experience with finance-related data marts (e.g. forecasting, P&L)
Exposure to predictive analytics and building machine learning-ready datasets

Ready to take the next step in your data engineering career? Apply now and be part of a forward-thinking team pushing the boundaries of Azure-based data solutions.

Remote working/work at home options are 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.

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.

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.