Jobgether
Spontaneous Application - Data Engineer

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This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Spontaneous Application - Data Engineer based in United Kingdom.
This is a spontaneous opportunity for an experienced Data Engineer interested in solving complex data challenges within a fast-growing technology environment.
You will design and maintain the infrastructure that enables large-scale data collection, transformation, storage, and analysis.
Your work will directly support business decision-making, machine learning initiatives, and the development of data-driven products.
You will collaborate closely with software engineers, ML engineers, data analysts, product teams, and other stakeholders to turn data requirements into reliable solutions.
The role offers exposure to diverse technical challenges, from building scalable pipelines to optimizing data quality and performance.
You will join an engineering-focused environment that values technical excellence, ownership, problem-solving, and meaningful customer impact.
As a spontaneous application, the opportunity may not be immediately prioritized, but strong profiles are reviewed regularly for current and future engineering needs.
Accountabilities
- Design, build, and maintain scalable data pipelines for collecting, storing, transforming, and processing data from multiple sources.
- Develop and maintain robust data models and schemas that support analytics, reporting, machine learning, and product development.
- Create, maintain, and optimize ETL processes that extract, transform, and load data into cloud-based data warehouses.
- Work closely with ML engineers, data analysts, software developers, product teams, and other stakeholders to understand data requirements and deliver appropriate technical solutions.
- Monitor data pipelines and processes to maintain high standards of data quality, reliability, availability, and performance.
- Identify bottlenecks and optimize data infrastructure and processing workflows as data volumes and product requirements grow.
- Contribute to the design of the broader data architecture, ensuring that pipeline components and cloud infrastructure work together effectively.
- Help establish reliable and accessible data foundations that enable data-driven business decisions and machine learning models.
- Participate in solving complex engineering challenges across data processing, infrastructure, and large-scale data systems.
- Contribute ideas and technical expertise to improve data capabilities and support ongoing product innovation.
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
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical discipline.
- At least 3 years of professional experience as a Data Engineer or in a comparable data-focused engineering role.
- Strong programming skills in Python, Java, or a similar programming language.
- Solid knowledge of SQL and data modeling principles.
- Professional experience with cloud-based data warehousing technologies such as Amazon Redshift, Google BigQuery, or equivalent platforms.
- Experience with data processing and ETL technologies such as Spark, Flink, Databricks, Snowflake, or similar tools.
- Familiarity with messaging and event-streaming systems such as Kafka, RabbitMQ, or equivalent technologies.
- Good understanding of cloud infrastructure and how different components of a modern data pipeline interact.
- Strong analytical and problem-solving abilities, with the capacity to investigate complex technical issues and develop scalable solutions.
- Excellent communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.
- Comfortable working in a fast-paced, evolving environment where ownership and initiative are highly valued.
- Ability to work from a location within approximately the GMT-3 to GMT+2 time zones.
Benefits
- Competitive salary.
- Health insurance.
- Stock options.
- Remote working environment.
- Opportunity to work within a highly technical and engineering-focused team.
- Exposure to challenging data, machine learning, infrastructure, and product engineering problems.
- Strong opportunities for professional growth and learning within a rapidly scaling technology company.
- Collaborative work environment with strong team spirit and a high degree of technical ownership.
- Annual company trip to a secret destination.
- Opportunity to contribute to innovative, data-driven products with meaningful customer impact.


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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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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