Data Engineer

Searchability®
Manchester
4 months ago
Create job alert
  • Salary up to £60,000 + discretionary bonus
  • Hybrid working model with collaborative office environment
  • Work with Databricks, Spark Structured Streaming, Kafka (MSK), and AWS
  • Apply online or contact Chelsea Hackett via
ABOUT THE CLIENT

Due to continued growth, we’re seeking a skilled Data Engineer to join an established organisation at the forefront of building modern, data-driven platforms. The business is investing heavily in its data ecosystem and is focused on delivering real-time insights and trusted analytics that support teams across product, finance, marketing, and compliance.

This is an excellent opportunity to work with modern cloud data technologies and play a key role in shaping a scalable, secure, and high-performance data platform.

WHAT WILL YOU BE DOING?

As a Data Engineer, you will design, build, and optimise scalable data pipelines within a Databricks Lakehouse environment. You’ll work with both streaming and batch data pipelines using technologies such as Apache Spark Structured Streaming, Delta Live Tables, and Kafka, ensuring data flows efficiently and reliably across the organisation.

Working closely with BI, product, and engineering teams, you will help deliver high-quality, governed data that supports analytics, reporting, and operational decision-making. You’ll also play a key role in enabling business intelligence through high-performance data models and integrations with reporting tools.

You’ll monitor and optimise pipeline performance, implement CI/CD processes for data workflows, and maintain strong governance and security standards across the data platform. Documentation, observability, and cost optimisation will also form part of your responsibilities as you contribute to the ongoing development of the organisation’s data ecosystem.

OUR BENEFITS:
  • Competitive basic salary
  • Discretionary bonus scheme
  • Company shares option plan
  • Contributory pension scheme
  • Life insurance (4x basic salary)
  • Health cash plan
  • Generous holiday allowance including bank holidays
  • Study support and clear progression opportunities
  • Collaborative office environment with regular social and charity events
  • And Much More!!!
DATA ENGINEER – ESSTENTIAL SKILLS
  • Strong experience with Databricks and Apache Spark (PySpark or Scala)
  • Experience building streaming and batch pipelines using Spark Structured Streaming
  • Hands‑on experience with Kafka (MSK) and real‑time data ingestion
  • Strong understanding of Delta Lake, Delta Live Tables, and Medallion Architecture
  • Solid AWS experience including services such as S3, Glue, Lambda, Batch, and IAM
  • Proficiency in Python and SQL for data engineering and analytics
  • Experience implementing CI/CD pipelines (GitHub Actions, Jenkins, or Azure DevOps)
  • Strong Git and version control practices
  • Experience tuning and optimising Spark workloads

Please either apply by clicking online or emailing me directly . By applying to this role you give express consent for us to process and submit (subject to required skills) your application to our client in conjunction with this vacancy only.

KEY SKILLS


#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 Engineering Employers to Watch in 2026: UK and Global Companies Driving the Data Revolution

Data engineering is at the heart of the digital economy, transforming raw data into actionable insights, powering analytics, AI systems, and cloud infrastructure. As the UK and global markets continue to invest heavily in data platforms, pipelines, and real-time analytics, demand for skilled data engineers is growing rapidly. For professionals exploring opportunities on www.DataEngineeringJobs.co.uk , the critical question is: which companies are expanding, hiring, and shaping the future of data-driven business? This article highlights new data engineering employers to watch in 2026, including UK startups, scale-ups, and international firms expanding in the UK.

How Many Data Engineering Tools Do You Need to Know to Get a Data Engineering Job?

If you’re aiming for a career in data engineering, it can feel like you’re staring at a never-ending list of tools and technologies — SQL, Python, Spark, Kafka, Airflow, dbt, Snowflake, Redshift, Terraform, Kubernetes, and the list goes on. Scroll job boards and LinkedIn, and it’s easy to conclude that unless you have experience with every modern tool in the data stack, you won’t even get a callback. Here’s the honest truth most data engineering hiring managers will quietly agree with: 👉 They don’t hire you because you know every tool — they hire you because you can solve real data problems with the tools you know. Tools matter. But only in service of outcomes. Jobs are won by candidates who know why a technology is used, when to use it, and how to explain their decisions. So how many data engineering tools do you actually need to know to get a job? For most job seekers, the answer is far fewer than you think — but you do need them in the right combination and order. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable and employable rather than overwhelmed.

What Hiring Managers Look for First in Data Engineering Job Applications (UK Guide)

If you’re applying for data engineering jobs in the UK, the first thing to understand is this: Hiring managers don’t read every word of your CV. They scan it. They look for signals of relevance, credibility, delivery and collaboration — and if they don’t see the right signals quickly, your application may never get a second look. In data engineering, hiring managers are especially focused on whether you can build and operate reliable, scalable data systems, handle real-world data challenges and work effectively with analytics, BI, data science and engineering teams. This guide breaks down exactly what they look at first in your application — and how to shape your CV, portfolio and cover letter so you stand out.