Impellam Group
Senior Data Engineer

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Senior Data Engineer
Department: Platform Technology
Location: Manchester
Reporting to: Engineering Manager
Overview
We're looking for a Senior Data Engineer who's ready to get stuck into any problem, across any part of the technology landscape. You'll bring a can-do attitude and enjoy stepping outside your comfort zone to solve problems, large and small.
You'll help improve our platform by working with the team to build tooling and processes that the development and test teams use to drive performance, productivity, and best practice. You'll also work within the team to enhance existing features across the full stack of our platform, ensuring delivery on time, to the right approach, and to the standards set by the development leads.
Key Responsibilities
- Design, develop and maintain data pipelines and ETL processes using AWS services such as AWS Glue, AWS Lambda and AWS S3
- Support the migration of the existing Data Warehouse from SQL Server to AWS, via S3 and Redshift
- Develop and implement data quality checks and validation procedures
- Design and implement best-practice data lakehouse architectures and data warehousing solutions
- Collaborate with data scientists and analysts to support deployment of machine learning and advanced analytical solutions
- Develop and maintain data documentation and operational procedures
- Investigate and resolve data quality issues and performance bottlenecks
- Stay abreast of the latest data technologies and industry best practice
- Mentor junior data engineers and provide technical guidance to other team members where applicable
- Contribute to the development and improvement of data platform best practice
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.
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.
This list is not exhaustive; you may be required to undertake additional duties, not listed, that are considered reasonable and aligned to your role.
Essential Experience & Skills
- Experience: 5+ years' significant commercial experience as a Data Engineer in a high-transactional, high-volume data environment, ideally within betting, gaming or fintech
- Programming: Strong proficiency in Python or Scala for data manipulation, automation and pipeline development
- Cloud: Extensive hands-on experience with a major cloud provider, particularly AWS, including Glue, Lambda and S3
- Data processing: Expertise in big data processing frameworks such as Apache Spark, plus experience with real-time streaming technologies like Apache Kafka
- SQL: Expert-level SQL for complex data querying, manipulation and optimisation within a data warehouse environment
- ETL/ELT: In-depth knowledge of ETL/ELT methodologies and tools, with experience designing and building efficient data pipelines
- Communication: Excellent communication and collaboration skills, with the ability to solve complex technical data problems logically and clearly


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Desirable Experience & Skills
- Experience with real-time sports betting data, game stats or fantasy sports
- Familiarity with DevOps principles and CI/CD tools (e.g. Terraform, Jenkins) for deploying and managing data infrastructure
- Experience with dimensional modelling and designing robust data schemas for analytical use cases
- Experience designing and implementing modern data lakehouse architectures
- Familiarity with monitoring/alerting tools (e.g. Grafana, Datadog) for data pipelines
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