Jobgether
Data Engineer

How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Job Opportunity: Data Engineer
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer based in United Kingdom.
As a Data Engineer, you will play a key role in building and maintaining the data infrastructure that powers machine learning, analytics, and business initiatives.
- Design scalable batch and near-real-time pipelines capable of handling millions of data changes every day.
- Ensure data remains accurate, consistent, reliable, and readily available across the organization.
- Collaborate closely with data scientists, MLOps engineers, product owners, and BI analysts to translate business needs into robust data solutions.
- Work in a remote-first environment with flexible working hours and a strong focus on autonomy and collaboration.
This is an opportunity to contribute to a rapidly growing, data-intensive environment while working with modern cloud and data technologies.
Accountabilities
- Data pipeline development: Design, develop, test, optimize, and maintain scalable batch ETL and near-real-time data pipelines capable of processing high-volume data sources.
- Data architecture: Build and evolve reliable data architectures that support machine learning, data science, business intelligence, and operational requirements.
- Data quality: Ensure data is accurate, consistent, reliable, and fit for downstream analytical and operational use.
- Scalability and optimization: Identify opportunities to improve internal processes, optimize data delivery, and redesign infrastructure to support increasing scale and complexity.
- API integrations: Develop and maintain new API integrations to accommodate growing data volumes and evolving business requirements.
- Cross-functional collaboration: Work closely with data scientists, MLOps engineers, product owners, and BI analysts to understand business processes, system architecture, and specific product needs.
- Data infrastructure: Contribute to the development and maintenance of data platforms, databases, integrations, and cloud infrastructure supporting production workloads.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Requirements
- Education: Bachelor’s degree or equivalent practical experience in Computer Science, Engineering, Mathematics, or a related technical discipline.
- Professional experience: 3+ years of experience in data engineering, data platforms, business intelligence, or a related field.
- Data-centric applications: Proven experience implementing data warehouses, operational data stores, data integration solutions, or similar data-focused applications.
- Database expertise: Experience working with large-scale production relational and NoSQL databases.
- Data modeling: Strong understanding and practical experience with data modeling principles.
- Architecture knowledge: General understanding of modern data architectures and event-driven architectures.
- SQL: Strong proficiency in SQL for querying, transforming, and analyzing data.
- Programming: Familiarity with at least one scripting language, preferably Python.
- Data technologies: Hands-on experience with Apache Airflow and Apache Spark.
- Cloud platforms: Solid understanding of AWS data services, including S3, Athena, EC2, Redshift, EMR, EKS, RDS, and Lambda.
- Machine learning: Understanding of machine learning models is an advantage.
- Containerization: Familiarity with Docker, Kubernetes, or similar containerization and orchestration technologies is beneficial.
- Industry knowledge: Experience or knowledge of the gaming industry is a plus.
- Collaboration: Strong communication skills and the ability to work effectively with technical and business stakeholders across multiple disciplines.


Get help with your application
Your very own career expert that helps elevate your application to the next level.
Benefits
- Remote-first environment: Work remotely with a strong focus on flexibility, autonomy, and sustainable working practices.
- Competitive compensation: Competitive salary with individual performance-based bonuses paid quarterly.
- Paid leave: 28 days of paid annual leave.
- Flexible working hours: Core working hours from 10:00 AM to 3:00 PM in your local time zone, with flexibility outside these hours.
- Additional bonuses: Opportunities to earn referral bonuses and flash bonuses.
- Quality equipment: Access to high-quality, professional equipment to support effective remote work.
- Annual retreats: Company retreats designed to encourage collaboration, networking, and stronger connections across the team.
- Professional growth: Exposure to large-scale data engineering challenges, modern cloud technologies, and cross-functional initiatives.
How Jobgether works
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
#LI-CL1
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Location