6 of 6 Permanent Parquet Jobs in London

data collection Solid understanding of data modelling best practices for analytics and dashboards Confidence working with large, complex datasets across multiple formats (CSV, JSON, Parquet, databases, APIs) Strong problem-solving skills and the ability to diagnose and resolve data issues Excellent communication skills and experience working with cross-functional ...

implement production-grade REST APIs using Python (FastAPI) to manage complex financial data submissions. ● Design secure ingestion pipelines for large-scale datasets (CSV/Parquet), leveraging S3, presigned URLs, automated webhooks, and high-performance data libraries such as Polars or Pandas. ● Develop sophisticated backend logic for consensus workflows, regional ...

stack. AI Integration: Leverage Claude and LLMs for signal extraction, code optimization, and autonomous strategy refinement. High-Performance Computing: Implement predicate pushdown and efficient Parquet/Arrow storage to ensure backtests on decades of data run in minutes, not days. Options Logic: Programmatically handle Greeks, volatility surfaces, and risk ...

normalise high-velocity time-series datasets from multiple external sources ⚙️ Work heavily in Python with a modern stack including DuckDB and Polars (plus Parquet/PyArrow ) 🧩 Orchestrate workflows and improve reliability (they use Temporal — similar orchestration experience is fine) ✅ Improve data integrity and visibility: validations, automated checks, backfills, monitoring … client-facing outputs (dashboards/PDF/Plotly — least important) What’s in it for you? 📌 Modern data stack – DuckDB/Polars + Parquet/Arrow in a genuinely hands-on environment 📈 Ownership & impact – You’ll be close to the data flows and have real influence on performance ...

/low level performance Skills: 2 - 15 years of experience as a C++ Developer Strong knowledge of optimization/performance Knowledge of Arrow/Parquet is a plus Experience working with Boost ASIO is a plus An interest in Rust is a nice plus Experience working at a large ...

automated test suites Writing and maintaining: API tests Integration tests End-to-end workflow tests Validating: Data ingestion flows File-based workflows (CSV/Parquet) Region-specific and customer-isolated data paths Testing error cases, edge cases, and failure modes Ensuring backward compatibility of APIs and schemas Tooling & Process … Client's Tech Stack (Context) Backend: Python 3.11+, FastAPI Frontend: TypeScript, React Infra: AWS (ECS/Fargate, S3, RDS, CloudFront) Data: PostgreSQL, CSV/Parquet CI/CD: GitLab CI IaC: Terraform Testing: Pytest, Postman/Newman, custom scripts You don’t need to know everything — but you should ...