
How to Get a Better Data Engineering Job After a Lay-Off or Redundancy
Redundancy can be unexpected and unsettling, especially in a field as technically demanding as data engineering. But the good news is: your skills are still in high demand. The UK continues to see strong growth in data infrastructure, cloud analytics, machine learning pipelines, and data governance roles.
Whether you're a big data engineer, ETL specialist, cloud data platform expert, or someone working in real-time streaming and pipelines, there are new opportunities to rebuild and rebrand your career.
This guide is designed to help UK-based data engineers bounce back after a redundancy, with a step-by-step roadmap to relaunch into a stronger, better-aligned role.
Contents
Understanding Redundancy in Data Engineering
Step 1: Reset and Refocus
Step 2: Clarify Your Skills and Preferred Tech Stack
Step 3: Update Your CV and GitHub Portfolio
Step 4: Optimise LinkedIn and Showcase Projects
Step 5: Reach Out to Recruiters and Hiring Managers
Step 6: Apply Intelligently and Track Progress
Step 7: Upskill in High-Demand Tools
Step 8: Explore Contract, Hybrid and Remote Roles
Step 9: Take Care of Your Finances and Wellbeing
Bonus: Top UK Employers Hiring Data Engineers in 2025
Final Thoughts: Redundancy as Redirection
Understanding Redundancy in Data Engineering
Even data teams get restructured. Redundancy is not a reflection of your technical value—it’s often a result of cloud budget shifts, platform migrations, or company-wide changes.
The market still needs skilled engineers who can build, optimise, and scale data pipelines across industries like finance, retail, logistics, healthcare and government.
Step 1: Reset and Refocus
Start by processing what happened:
Acknowledge your success and experience
Identify what you liked and disliked about your last role
Set your sights on roles that align with your strengths, values and career goals
This is a chance to reposition yourself.
Step 2: Clarify Your Skills and Preferred Tech Stack
List out your core competencies:
Are you strongest in batch ETL, streaming, or warehousing?
What cloud platforms do you specialise in (AWS, Azure, GCP)?
Which tools do you know well? (e.g. Spark, Kafka, Airflow, dbt, Snowflake, BigQuery)
This helps you match quickly with relevant roles.
Step 3: Update Your CV and GitHub Portfolio
Your CV should:
Begin with a clear summary (e.g. “AWS Data Engineer with 5+ years' experience building scalable, secure pipelines”)
Emphasise results (e.g. “Reduced query time by 60% through warehouse optimisation”)
Highlight tools, languages and platforms used
Link to GitHub or project documentation where possible
Make your work easy to assess.
Step 4: Optimise LinkedIn and Showcase Projects
LinkedIn is critical in data hiring.
Profile Tips:
Headline: “Data Engineer | BigQuery, dbt, Airflow | Open to Work”
About section: Include experience, strengths, cloud stack, and what kind of role you’re seeking
Feature personal or team projects, certifications, blog posts
Sample LinkedIn About Section:
Data Engineer | Cloud Pipelines | BigQuery | Open to Work
I’m an experienced data engineer with 5+ years designing robust data pipelines across cloud platforms. Redundancy gave me the chance to refocus, and I’m now seeking a new opportunity to work on meaningful data infrastructure projects that drive insight and scale.
Stack: Airflow, Python, dbt, Snowflake, Terraform, GCP, Git, CI/CD
Let’s connect if you’re hiring for data engineering roles or collaborating on data transformation projects.
Step 5: Reach Out to Recruiters and Hiring Managers
Be proactive in building connections:
Recruiter Message Example:
Subject: Data Engineer | Available Immediately | Cloud & ETL
Hi [Recruiter’s Name],
I’m looking for a new data engineering role following a recent redundancy. My background includes building cloud-native ETL pipelines, stream processing, and cost-optimised data infrastructure.
Please find my CV and GitHub link attached. I’d appreciate hearing about any relevant roles you’re working on.
Best regards,
[Your Name]
[LinkedIn]
[GitHub]
[CV attachment]
Hiring Manager Follow-Up Example:
Subject: Application – Data Engineer Role at [Company Name]
Dear [Hiring Manager],
I recently applied for the Data Engineer role at your company and wanted to share my enthusiasm. I bring hands-on experience with GCP pipelines, warehouse optimisation, and dbt modelling. I’m currently available following a restructure and would welcome the chance to contribute.
Please find my CV attached. I’d be happy to discuss the role further.
Kind regards,
[Your Name]
Step 6: Apply Intelligently and Track Progress
Avoid applying everywhere at once. Instead:
Focus on 10–15 high-fit roles
Tailor each CV using keywords from job specs
Keep a tracker of where you applied, dates, and follow-ups
Revisit roles weekly to follow up with hiring contacts
Step 7: Upskill in High-Demand Tools
Use this period to boost your stack:
Earn or update certifications (Google Data Engineer, Azure Data Fundamentals)
Learn tools like dbt, Great Expectations, Dagster, or Iceberg
Take short courses on DataCamp, Udemy, Coursera or Pluralsight
Document new projects in GitHub or write about them on Medium
Step 8: Explore Contract, Hybrid and Remote Roles
Contract work can provide income and exposure while job hunting:
Look at freelance data gigs via Upwork or Toptal
Check UK remote-friendly data roles on www.dataengineeringjobs.co.uk
Explore hybrid positions in London, Manchester, Bristol or Leeds
Step 9: Take Care of Your Finances and Wellbeing
Redundancy is stressful—don’t overlook self-care:
Apply for redundancy pay, Universal Credit or Jobseeker’s Allowance
Seek free budgeting advice via Citizens Advice or MoneyHelper
Structure your day with job search time, skill building, and rest
Stay connected to peers and meetups to avoid isolation
Bonus: Top UK Employers Hiring Data Engineers in 2025
Spotify (London Data Team)
Sky
NHS England (Data Platforms)
Monzo & Starling Bank
The Trade Desk
ASOS
Sainsbury's Tech
Zoopla
GOV.UK / GDS
Booking.com (UK roles)
Babylon Health
Palantir UK
YouGov
BT
Deliveroo
Explore live data engineering jobs on www.dataengineeringjobs.co.uk
Final Thoughts: Redundancy as Redirection
Being made redundant is difficult, but it can also be the start of a better chapter. Use this time to reset, refocus, and build the career you truly want in data engineering.
Your skills are valuable. Your next role might be your best yet.
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