Data Engineer at Solve Intelligence
May no longer be active — verify on the employer site
At a glance
- Company
- Solve Intelligence
- Location
- London, United Kingdom
- Work arrangement
- On-site
- Employment type
- Full-time
- Experience
- 2–5 years
- Working hours
- 40 hours
- Visa sponsorship
- Offered, according to the listing
- Posted
✨ The Stack take on this Solve Intelligence job
- 🏢 Solve Intelligence has 6 jobs here, 1 with visa sponsorship see all
- 📊 13 Data Engineer jobs in the United Kingdom in the last 60 days see them
- 🛂 Skilled Worker visa. Standard minimum salary: £41,700 a year guide
- 💡 No salary shown. Ask Solve Intelligence if it is above the minimum.
Updated 2026-11-03, from our data and official sources.
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About the role
Responsibilities:
- Build and operate high-throughput, resumable ingestion pipelines with incremental updates, monitoring and failure recovery.
- Parse and extract structured content from diverse document types while preserving metadata and handling malformed records and evolving schemas.
- Design schemas, indexes and partitioning for keyword, vector and structured search over tens to hundreds of millions of records.
- Link and reconcile records across patents, scientific literature and other sources; preserve provenance, dates and versions.
- Profile and tune parsing, ingestion, database builds and queries; diagnose CPU, memory and storage I/O bottlenecks and optimise for throughput, latency and cost.
- Collaborate closely with AI researchers and product engineers; take end-to-end ownership from source acquisition to serving queries.
Requirements:
- Strong proficiency in Python and SQL and demonstrable experience operating production databases.
- Hands-on experience building and running production data pipelines for large, messy datasets.
- Practical experience operating search systems (keyword and vector) over large document collections.
- Solid understanding of schema design, indexing, query optimisation and performance profiling.
- Proven track record of diagnosing and fixing performance bottlenecks in live systems through measurement and tuning.
- Nice-to-have: experience with PostgreSQL/pgvector, OpenSearch/Elasticsearch, Spark/Delta Lake, AWS, NoSQL or systems languages (Rust/C++).
Responsibilities
You will build and operate high-throughput data ingestion pipelines and search systems for AI products. This involves managing the full lifecycle of data from source acquisition to serving queries while optimizing for performance and scalability.
Requirements
You must have strong proficiency in Python and SQL with extensive experience operating production data pipelines and search systems. A proven track record of diagnosing performance bottlenecks and managing large-scale datasets is essential.
Key skills
- Python — in 1173 other listings on The Stack
- SQL — in 527 other listings on The Stack
- Data pipelines — in 113 other listings on The Stack
- Search systems — in 3 other listings on The Stack
- Schema design — in 22 other listings on The Stack
- Indexing — in 2 other listings on The Stack
- Query optimization — in 11 other listings on The Stack
- Performance profiling — in 8 other listings on The Stack
- PostgreSQL
- Pgvector
- OpenSearch
- Elasticsearch
- Spark
- Delta Lake
- AWS
- NoSQL
On The Stack (as of 2026-11-03)
Frequently asked questions about Solve Intelligence
Is this Data Engineer role still open?
It was posted on 2026-09-16. Listings more than 30 days old may no longer be active, so check Solve Intelligence's site before applying.
Does Solve Intelligence offer visa sponsorship?
This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on Solve Intelligence's site.
Where is this role located?
The listing gives the location as London, United Kingdom. It is marked on-site.
What skills does this role ask for?
The listing names: Python, SQL, Data pipelines, Search systems, Schema design, Indexing, Query optimization, Performance profiling, PostgreSQL, Pgvector, OpenSearch, Elasticsearch, Spark, Delta Lake, AWS, NoSQL.