Boost Talent ltd
Senior Data Engineer (Python)

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Role Overview
We're partnering with a data-driven technology organisation looking for a Senior Data Engineer to help shape the way complex, high-value datasets are collected, transformed, managed and delivered across a global business.
This is a hands-on engineering role focused on building modern data platforms, developing scalable data pipelines and creating trusted data products that support both internal teams and external customers. You'll work with large and complex datasets, helping to establish the architecture, tooling and engineering standards that underpin a growing cloud-based data ecosystem.
You'll join a collaborative engineering environment where teams take ownership of solutions from design through to production. The role offers significant influence over platform strategy, technical direction and engineering best practice, providing the opportunity to shape how data is managed, discovered and consumed across the organisation.
For engineers who enjoy solving large-scale data challenges, improving data accessibility and building reliable systems that directly impact products and customers, this represents an excellent opportunity to make a meaningful contribution.
What You'll Be Doing
- Designing, building and maintaining scalable ETL/ELT pipelines and data processing workflows
- Developing and optimising data products that transform complex datasets into trusted, consumable assets
- Building Python-based services and tooling that support data ingestion, transformation and delivery
- Contributing to the evolution of a modern cloud-native data platform
- Defining and promoting standards around data quality, governance, metadata and observability
- Working closely with software engineering, platform and product teams to improve data accessibility and reliability
- Supporting production data systems, monitoring and operational excellence
- Contributing to architectural decisions and helping drive engineering best practice across the organisation
- Mentoring colleagues and fostering a strong engineering culture
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.
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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.
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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.
Skills Required
We're particularly interested in experienced Data Engineers who combine strong Python development skills with expertise in building modern cloud-based data platforms.
Essential Experience
- Strong commercial experience as a Data Engineer, Data Platform Engineer or Python Engineer working with large-scale datasets
- Advanced Python development experience
- Designing and developing ETL/ELT pipelines and modern data platforms
- Experience with AWS-based data platforms
- AWS services including Glue, Step Functions, Athena, S3 and serverless architectures
- Data modelling, transformation and orchestration tooling such as dbt
- Working with modern analytical storage formats including Parquet and Iceberg
- Building robust data ingestion and transformation workflows
- Data quality frameworks, schema evolution and metadata management
- Experience with distributed data processing and large-scale datasets
- Understanding of REST APIs and data integration patterns
- Strong software engineering principles, including testing, maintainability and security
- Monitoring, observability and operational support for production data platforms


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Desirable Experience
- Event-driven architectures, messaging and streaming technologies
- OpenSearch, graph databases or knowledge graph technologies
- Data discovery, catalogue or lineage platforms
- Experience building backend services using Python
- Experience working within agile, cross-functional engineering teams
Why Apply?
- Opportunity to influence the evolution of a strategic data platform
- Work with complex, high-value datasets at scale
- Significant ownership and technical autonomy
- Collaborative engineering culture with strong technical standards
- Exposure to modern cloud, data engineering and platform technologies
- Opportunity to shape engineering best practices and platform direction
A Little Note From Us
Boost Talent is committed to creating an inclusive recruitment experience and supporting equal opportunities throughout the recruitment process. We welcome applications from people of all backgrounds and will gladly discuss any reasonable adjustments you may need to help you feel supported throughout the process.
While we'd genuinely love to reply to everyone individually, we often receive a high number of applications for the roles we advertise. If your experience aligns with the opportunity, a member of our team will be in touch to discuss the role.
Best of luck!
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