
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Sparta Global Hiring: Data Engineer
Sparta Global is hiring a Data Engineer with 2-5 years’ commercial experience to support delivery within a market-leading media client based in Leeds.
Summary
Working within the Reporting & Data Enablement team, the Data Engineer designs, builds and operates the reliable data pipelines and curated datasets that underpin reporting and analytics. The role acquires, transforms and validates data from multiple internal and partner sources, ensuring quality, lineage and security so that analysts, report developers and leaders can rely on a single source of truth.
Key Responsibilities
- Design, build and maintain ingestion and transformation pipelines to create model-ready, governed datasets for reporting and analysis.
- Implement data quality checks (schema validation, reconciliation, anomaly detection) and monitoring/alerting for refresh health and SLA adherence.
- Develop reusable transformation patterns and shared components (e.g., dimension/lookup handling, incremental loads, SCDs) to improve consistency and speed.
- Work with semantic-layer and report developers to separate modelling from presentation and to uphold consistent KPI definitions.
- Follow Dev → Test → Prod workflows using deployment pipelines and version control; publish clear change logs and release notes.
- Optimise pipelines for performance, reliability and cost (partitioning, scheduling, parallelism; efficient storage and compute choices).
- Document lineage, data dictionaries, refresh cadence, ownership and support routes; ensure discoverability via the catalogue.
- Apply data governance and security (e.g., role-based access, PII handling, audit trails) and ensure alignment with organisational policies.
- Collaborate with Technology Data Engineering to ensure platform readiness, access, standards alignment and smooth incident/change handling.
- Contribute to enablement by sharing patterns, writing how-to guides and supporting show-and-tell sessions with analysts and report developers.
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.
Essential Skills & Experience


Get help with your application
Your very own career expert that helps elevate your application to the next level.
- Proven experience in data engineering or analytics engineering (c. 2 years) delivering reliable, governed datasets for BI and analytics.
- Strong SQL and practical experience with a cloud data platform (e.g., AWS/Azure/Fabric or equivalent) and orchestration tooling.
- Hands-on with ELT/ETL patterns, incremental loads, performance tuning and data quality testing.
- Working knowledge of Power BI data model requirements and how pipeline design impacts report performance.
- Evidence of documentation, version control and release/change discipline.
- Clear communication and collaboration with Technology and Insight teams; ability to translate requirements into technical designs.
“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
Skills
Location