Data Engineer (Python)

London
3 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

About the RoleWe are looking for a Python Data Engineer with strong hands-on experience in Behave-based unit testing, PySpark development, Delta Lake optimisation, and Azure cloud services. This role focusses on designing and deploying scalable data processing solutions in a containerised environment, emphasising maintainable, configurable, and test-driven code delivery.
Key Responsibilities

Develop and maintain data ingestion, transformation, and validation pipelines using Python and PySpark.
Implement unit and behavior-driven testing with Behave, ensuring robust mocking and patching of dependencies.
Design and maintain Delta Lake tables for optimised query performance, ACID compliance, and incremental data loads.
Build and manage containerised environments using Docker for consistent development, testing, and deployment.
Develop configurable, parameter-driven codebases to support modular and reusable data solutions.
Integrate Azure services, including:
Azure Functions for serverless transformation logic
Azure Key Vault for secure credential management
Azure Blob Storage for data lake operationsWhat We're Looking For

Proven experience in Python, PySpark, and Delta Lake.
SC Cleared
Strong knowledge of Behave for test-driven development.
Experience with Docker and containerised deployments.
Familiarity with Azure cloud services and data engineering best practices.
Ability to deliver scalable, maintainable, and testable solutions in a fast-paced environment.

If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.
If this job isn't quite right for you, but you are looking for a new position, please contact us for a confidential discussion about your career.

Hays Specialist Recruitment Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this job you accept the T&C's, Privacy Policy and Disclaimers which can be found at (url removed)

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.

Careers

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

If you’re aiming for a career in data engineering, it can feel like you’re staring at a never-ending list of tools and technologies — SQL, Python, Spark, Kafka, Airflow, dbt, Snowflake, Redshift, Terraform, Kubernetes, and the list goes on. Scroll job boards and LinkedIn, and it’s easy to conclude that unless you have experience with every modern tool in the data stack, you won’t even get a callback. Here’s the honest truth most data engineering hiring managers will quietly agree with: 👉 They don’t hire you because you know every tool — they hire you because you can solve real data problems with the tools you know. Tools matter. But only in service of outcomes. Jobs are won by candidates who know why a technology is used, when to use it, and how to explain their decisions. So how many data engineering tools do you actually need to know to get a job? For most job seekers, the answer is far fewer than you think — but you do need them in the right combination and order. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable and employable rather than overwhelmed.

Jobs

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

If you’re applying for data engineering jobs in the UK, the first thing to understand is this: Hiring managers don’t read every word of your CV. They scan it. They look for signals of relevance, credibility, delivery and collaboration — and if they don’t see the right signals quickly, your application may never get a second look. In data engineering, hiring managers are especially focused on whether you can build and operate reliable, scalable data systems, handle real-world data challenges and work effectively with analytics, BI, data science and engineering teams. This guide breaks down exactly what they look at first in your application — and how to shape your CV, portfolio and cover letter so you stand out.

Education

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

Data engineering has quietly become one of the most critical roles in the modern technology stack. While data science and AI often receive the spotlight, data engineers are the professionals who design, build and maintain the systems that make data usable at scale. Across the UK, demand for data engineers continues to rise. Organisations in finance, retail, healthcare, government, media and technology all report difficulty hiring candidates with the right skills. Salaries remain strong, and experienced professionals are in short supply. Yet despite this demand, many graduates with degrees in computer science, data science or related disciplines struggle to secure data engineering roles. The reason is not academic ability. It is a persistent skills gap between university education and real-world data engineering work. This article explores that gap in depth: what universities teach well, what they consistently miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data engineering.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.