Senior Data Engineer, Data Products & APIs
Summary
Builds and optimizes large-scale distributed data processing systems on AWS Databricks, designing pipelines and data lakes to ingest, validate, and monitor data from diverse sources for a fintech security company.
- Design, deploy, and maintain data-intensive pipelines and APIs that match real-world entities, relationships, and risk factors, including the deduplication and canonicalization logic behind corporate data, and the checks that validate the quality and consistency of that data.
- Build reusable Python packages and APIs, following software best practices, that expose reconciled entity data as a central service for other Kharon engineering teams.
- Help mature experimental ML models and agentic systems into production, including monitoring, evaluation harnesses, and version control.
- Take an active, big-picture role in driving improvement to Kharon’s technical architecture.
- Work at a fast, AI-assisted development pace (Claude, Cursor); prior LLM tool experience is not required, but comfort adapting to an agentic workflow is.
- Follow good engineering practices: documentation, diagrams, and unit/validation testing.
- Direct experience designing and deploying sophisticated data solutions, ideally including advanced models such as NLP, search algorithms, or graph analytics.
- Strong API design and ownership experience, ideally with FastAPI (Flask/Spring Boot acceptable).
- Strong Python fundamentals, including Pandas, PySpark, or Polars.
- SQL and relational database experience: schema design, access patterns, and query performance optimization.
- Experience designing and maintaining Python libraries used by other engineering teams.
- Experience with data pipeline technologies (Airflow, Kafka, AWS Glue, or equivalents).
- Strong verbal and written communication skills, with the ability to justify architectural decisions to both engineering and business stakeholders.
- Experience taking ML models from prototype to production, including monitoring, versioning, and evaluation.
- Experience with graph databases (Neo4j, Neptune) or graph-based data modeling.
- Familiarity with fuzzy-matching/entity-resolution libraries (Splink, Dedupe.io, Senzing, Zingg).
- Experience with Elasticsearch data and query modeling.
- Container-based deployment experience (Docker, Kubernetes).
- Interest or experience in geopolitics, sanctions compliance, or financial risk.
- Fully-sponsored private health insurance
- Pension plan with 3% employer contribution
- Annual leave plus bank holidays
You must have the right to work in the UK. Kharon is unable to offer visa sponsorship for this role.
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