proSapient
Data Engineer

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About the Role
Every day, somewhere in the world, important decisions are made. Whether it is a private equity company deciding to invest millions into a business or a large corporation implementing a new strategic direction, these decisions impact employees, customers, and other stakeholders.
Consulting and private equity firms come to proSapient when they need to discover knowledge to help them make great decisions and succeed in their goals. It is our mission to support them in their discovery of knowledge.
We help our clients find industry experts who can provide their knowledge via interview or survey; we curate this knowledge in a market-leading software platform; and we help clients surface knowledge they already have through expansive knowledge management.
We are looking for a Data Engineer to help build and scale the Knowledge Graph at the heart of our AI roadmap.
You will join the Data Foundation squad, building the pipelines that populate, maintain, and serve the graph as a reliable Content / Data product. This is a hands-on role for someone who enjoys meaningful data modelling challenges across entities, relationships, taxonomies, and versioning.
Key Duties
- Graph Construction Pipelines:
- Build ingestion and transformation pipelines that populate the Knowledge Graph from internal systems, enrichment outputs, and third-party sources.
- Implement entity resolution and linking logic in production.
- Manage late-arriving data, conflicting sources, and graph schema changes over time.
- Serving the Graph:
- Build query and serving layers used by search, matching, and data product teams.
- Model the graph for analytical and application use cases across systems such as BigQuery, PostgreSQL, and Elasticsearch / OpenSearch.
- Support external-facing data products with reliable export and delivery pipelines.
- Quality & Operations:
- Implement data quality checks, lineage, and monitoring across graph pipelines.
- Own production operations, including alerting, backfills, and incremental reprocessing.
- Contribute to data contracts so downstream teams can rely on the graph.
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.
Key Skills
- 3+ years building production data pipelines.
- Strong Python and SQL skills, with experience writing clean, production-ready code.
- Experience with PostgreSQL or other relational databases.
- Strong data modelling skills, including schema design for evolving requirements.
- Experience integrating messy, multi-source data, including deduplication and normalization.
- Hands-on experience with Elasticsearch / OpenSearch or a comparable serving layer.
- Comfortable with testing, code review, CI, and operating your own pipelines.


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Nice to Have
- Experience with graph databases, graph data modelling, taxonomies, or ontologies.
- Experience with entity resolution at scale.
- Experience with BigQuery, Kafka, dbt, or similar data platforms and frameworks.
- Familiarity with Docker, Kubernetes, and cloud environments such as AWS or GCP.
What We Can Offer You
- Tenure gifts, including vouchers, extra holiday, and sabbaticals for each year of employment.
- Health insurance through Vitality.
- Remote working for up to 20 days each year, giving you flexibility and a change of scenery.
- Employee Assistance Programme with personalized health and wellbeing advice from specialist teams.
- Enhanced maternity and paternity pay.
- 25 days’ annual leave plus bank holidays, including a week’s closure over Christmas.
- MyMindPal app for online mental fitness support.
- Corporate events, from quarterly gatherings to annual winter and summer parties.
We are committed to building an inclusive workplace. Marginalised groups are often less likely to apply unless they meet every requirement listed, so if you are interested in this role but do not tick every box, we encourage you to apply anyway — it could still be a great match.
“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
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