Data Analytics Engineer

Morson Edge (Technology)
London
2 weeks ago
Create job alert

We are looking for a Data Engineer who will design and implement customer data solutions that enable personalised experiences while ensuring privacy, quality, and accessibility of customer information across all touchpoints.


Length: 12 months

Location: London, UK

Environment: Hybrid - 2-3 days in the office


Key responsibilities:


  • Develop and maintain dbt models that transform raw data into trusted datasets for analytics and business intelligence
  • Implement data quality tests and monitoring to ensure accuracy and reliability
  • Optimise query performance using effective data modelling and materialisation strategies
  • Establish and maintain documentation and data dictionaries for analytical models, KPI definitions and metrics frameworks
  • Conduct exploratory data analysis to identify trends, patterns, and anomalies in business performance
  • Build interactive dashboards and reports that empower self-service analytics
  • Design visualizations that clearly communicate complex data stories to both technical and non-technical audiences


What is required to be successful in this role:


  • Strong SQL skills with experience in complex data transformations, CTEs and window functions
  • Expertise with dbt and modern analytics engineering tools
  • Solid understanding of dimensional modelling and data warehousing concepts
  • Experience with Git-based workflows for version control and collaboration for analytics
  • Knowledge of data testing frameworks and quality assurance practices
  • Experience with Snowflake, Databricks, or similar data platforms
  • Proficiency in Looker or similar BI tools (Tableau, Power BI)

Related Jobs

View all jobs

Data Analytics Engineer

Data Analytics Engineer (Microsoft Fabric)

Data Analytics Engineer (Microsoft Fabric)

Data Analytics Engineer

Data Analytics Engineer

Data Analytics Engineer: Build AI-Driven Insights

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.