Data Engineer (Airflow)

Harnham
Manchester
10 months ago
Create job alert

Get AI-powered advice on this job and more exclusive features.

This range is provided by Harnham. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Direct message the job poster from Harnham

Building Data Engineering Teams Across the North of England and Midlands

DATA ENGINEER

PRIMARILY REMOTE UK

An established company in the Media/Advertising space is seeking a proactive Data Engineer to join their innovative team as they grow and invest.

THE COMPANY:

This company is currently investing in their data team and is looking for a Data Engineer to help gather requirements and build solutions. This is an exciting opportunity to help build out the data platforms and create frameworks to enable data-driven decision making across the business.

THE ROLE:

A Data Engineer will need to:

  1. Work closely with stakeholders across the business
  2. Manage data warehouse (gathering requirements and building solutions)
  3. Ensure alignment with data management and quality

YOUR SKILLS AND EXPERIENCE:

A successful Data Engineer will have the following skills and experience:

  1. Ability and experience interacting with key stakeholders
  2. Strong experience in SQL/Python
  3. Good understanding of Airflow/DBT
  4. Experience with GCP/AWS
  5. Background in CI/CD

THE BENEFITS:

You will receive a salary, dependent on experience. Salary is up to £60,000. On top of the salary, there are some fantastic additional benefits.

HOW TO APPLY:

Please register your interest by sending your CV to Molly Bird via the apply link on this page.

Seniority level

  • Entry level

Employment type

  • Full-time

Job function

  • Analyst

Industries

  • Data Infrastructure and Analytics

Referrals increase your chances of interviewing at Harnham by 2x.

Set job alerts for “Data Engineer” roles by signing in.

Locations include Manchester, Rochdale, Nelson, Warrington, Bolton, and surrounding areas in Greater Manchester and the North of England, with recent postings from 1 day to 3 months ago.


#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.