Data Engineer

RES
Glasgow
2 months ago
Create job alert
Data Engineer – Databricks and Python

Location: Glasgow, Scotland, United Kingdom


Employment type: Full-time | Seniority level: Associate


We are the world's largest independent renewable energy company, dedicated to providing affordable, zero‑carbon energy. As part of our Digital Solutions business, we are seeking a skilled Data Engineer with expertise in Databricks to build and optimise scalable data pipelines that enable data‑driven analytics and machine learning for our asset performance management software.


This is a 24‑month fixed‑term contract.


Responsibilities

  • Design, develop, and maintain robust data pipelines using DLT on Databricks.
  • Collaborate with software engineers, data scientists and platform engineers to understand data requirements and deliver high‑quality solutions.
  • Implement ETL/ELT processes to ingest, transform, and store data from various sources (structured and unstructured).
  • Optimize performance and cost‑efficiency of data workflows on Databricks.
  • Ensure data quality, integrity, and governance through validation, monitoring, and documentation.
  • Develop reusable components and frameworks to accelerate data engineering efforts.
  • Support CI/CD practices and automation for data pipeline deployment.
  • Stay current with Databricks features and best practices, and advocate for their adoption.

Knowledge

  • Solid understanding of data modelling, warehousing concepts, and distributed computing.
  • Familiarity with Delta Lake and Unity Catalog.
  • Knowledge of data governance frameworks and compliance standards (e.g., GDPR, HIPAA).

Skills

  • Strong programming skills in Python and SQL.
  • Experience with version control (e.g., Git) and CI/CD tools.
  • Excellent problem‑solving and communication skills, both written and oral.

Experience

  • Proven experience as a Data Engineer with hands‑on expertise in Databricks and DLT.
  • Experience with cloud data platforms, ideally Azure; experience with AWS or Google is an advantage.
  • Exposure to machine learning workflows and integration with ML models.
  • Delivering results working in a distributed, cross‑functional team.

Qualifications

  • Databricks certification (e.g., Databricks Certified Data Engineer Associate/Professional).

At RES we celebrate difference and believe that diverse perspectives drive innovation. We encourage applicants with different backgrounds, ideas and points of view to apply. That is why we have a strong commitment to equal opportunity and to creating a welcoming workplace for everyone, regardless of ethnicity, culture, gender, nationality, age, disability, sexual orientation, gender identity, marital or parental status, education, or social background.


We are an equal‑employment‑opportunity employer who strives for inclusion for all employees and applicants.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

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.