Data Engineer

Reply
London
6 months ago
Create job alert
Overview

Data Engineer role at Data Reply in London. You will design and develop high-performance big data applications, manage complex data sets, and work across the full development lifecycle.

Responsibilities
  • Translate functional requirements into technical requirements as a big data consultant
  • Design and develop high performing, end-to-end big data applications to process large volumes of data (batch and real-time) in a multi-tenancy cloud environment
  • Develop and implement tools for data acquisition, extraction, transformation, management, and manipulation of large and complex data sets
  • Participate in all aspects of development - design, development, build, deployment, monitoring and operations
  • Research and experiment with emerging technologies and industry trends to bring business value through early adoption
About the candidate
  • A minimum Bachelor’s degree in Computer Science or related IT discipline
  • 1-2 years’ experience with big data projects using SQL and Python
  • Experience with AWS and Databricks
  • Excellent communication skills with the ability to articulate complex information to varied audiences
  • Strong interest in pursuing a specialist career path as a Big Data Engineer
  • Solid understanding of Python concepts for data engineering (e.g., Pandas, NumPy, JSON, file handling)
  • Understanding of AWS cloud environments (S3, Lambda, RDS, AWS CDK or Terraform, DynamoDB)
  • Flexibility regarding local business travel
About Data Reply

Data Reply is the Reply Group company offering analytics and data processing services across industries, helping clients build data strategies and realise the value of their data. We provide bespoke solutions and in-house training to ensure clients realise the full value of their big data solutions.

Reply is an Equal Opportunities Employer and is committed to embracing diversity in the workplace. We provide equal employment opportunities to all employees and applicants and prohibit discrimination and harassment of any type. We also support reasonable adjustments in the recruitment process.

Seniority level
  • Associate
Employment type
  • Full-time
Job function
  • Consulting, Information Technology, and Engineering
Industries
  • IT Services and IT Consulting, Business Consulting and Services, Software Development


#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.