Pyspark Data Engineer

iO Associates - UK/EU
Newcastle upon Tyne
9 months ago
Applications closed

Related Jobs

View all jobs

Contract Data Engineer (Azure) - Agile IT Team

Senior Data Engineer (Python/PySpark & SQL)

Lead Data Engineer

Senior Data Engineer

Data Engineer

Data Engineer

PySpark Data Engineer | up to £450/day Inside | Remote with occasional London travel

We are seeking a PySpark Data Engineer to support the development of a modern, scalable data lake for a new strategic programme. This is a greenfield initiative to replace fragmented legacy reporting solutions, offering the opportunity to shape a long-term, high-impact platform from the ground up.

Key Responsibilities:
* Design, build, and maintain scalable data pipelines using PySpark 3/4 and Python 3.
* Contribute to the creation of a unified data lake following medallion architecture principles.
* Leverage Databricks and Delta Lake (Parquet format) for efficient, reliable data processing.
* Apply BDD testing practices using Python Behave and ensure code quality with Python Coverage.
* Collaborate with cross-functional teams and participate in Agile delivery workflows.
* Manage configurations and workflows using YAML, Git, and Azure DevOps.

Required Skills & Experience:
* Proven expertise in PySpark 3/4 and Python 3 for large-scale data engineering.
* Hands-on experience with Databricks, Delta Lake, and medallion architecture.
* Familiarity with Python Behave for Behaviour Driven Development.
* Strong understanding of YAML, code quality tools (e.g. Python Coverage), and CI/CD pipelines.
* Knowledge of Azure DevOps and Git best practices.
*Active SC clearance is essential- applicants without this cannot be considered.

Contract Details:
* 6-month initial contract with long-term extension potential (multi-year programme).
* Inside IR35.

This is an excellent opportunity to join a high-profile programme at its inception and help build a critical data platform from the ground up. If you are a mission-driven engineer with a passion for scalable data solutions and secure environments, we'd love to hear from you.

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.

Products

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.

Jobs

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.

Careers

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.

🍪 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.