Job Opportunities API

About 9fin 9fin is the AI platform powering global debt markets — the world’s largest asset class at over $145 trillion. Debt markets are vast, global, and mission-critical, yet still run on fragmented data, PDFs, and manual workflows. 9fin replaces this broken infrastructure with a single platform that centralises proprietary credit data, deep analysis, and high-value workflows across global markets. Today, 9fin powers teams at 300+ blue-chip institutions worldwide, including global banks, asset managers, private equity firms, law firms, and advisors. The business is scaling at exceptional speed, with rapid expansion in the US and best-in-class retention driven by deep workflow adoption. We’re at a defining inflection point. With proven product-market fit and strong, global market pull, 9fin is accelerating toward becoming the category-defining platform for debt markets worldwide. About the role We're building the data platform that powers both our internal analytics and, increasingly, our customer-facing data products — screeners, embedded analytics, and data feeds/sharing. This role owns the movement, storage, and productisation of data end to end: from ingesting high-volume operational data out of our Product Engineering services into the lake, to serving it back to customers under a production SLA. This is a platform and product leadership role, not an analytics or BI modelling role. Our Analytics team already owns dbt, the semantic layer, and internal BI — you partner with them and consume their definitions; you don't rebuild what they own. What you'll own - Ingestion — event-driven and CDC streams, stream processing (e.g. Flink), batch, and file-based vendor feeds (SFTP / managed file transfer), landing data from Product Engineering services into the lake - The lake / lakehouse — Parquet, Trino, table formats, partitioning, and the physical and analytical modelling underneath - The serving / cache tier — powering customer-facing screeners and analytics at production latency and concurrency - Data sharing and feeds — governed external delivery via Snowflake / Databricks (Delta Sharing), APIs, and file feeds - The reverse-ETL platform — pushing derived data back to operational systems and downstream tools - Data contracts and governance — schema governance, entitlements, and the classification controls that keep sensitive data (e.g. people data) off the customer edge What we're looking for - Has built and operated a customer-facing data product under an SLA — embedded analytics, a data-feed/API business, or a data-sharing product — not only an internal warehouse - Deep experience moving high-volume data in production: event-driven and CDC ingestion, stream processing (Flink), batch, file-based feeds, schema evolution, backfills - Strong on schema registries and contracts (Avro/Protobuf, evolution, breaking-change handling across producers and consumers) — not just dimensional modelling - Fluent in Parquet, Trino, streaming (Kafka/Flink), and lakehouse platforms (Snowflake/Databricks), and the throughput and cost engineering that comes with scale - Product and governance instincts: multi-tenancy, row-level entitlements, usage metering, and data classification - Bonus: experience in financial data, capital markets, or market-intelligence products (Bloomberg / S&P / 9fin-style). How you'll work Peer to the Head of Analytics — you own platform and external data products; they own meaning and internal BI. You consume their semantic layer as a contract, and neither team duplicates the other. Partner with Product Engineering (our Core and Market Vertical domain teams) as your data producers — defining versioned data contracts and a paved-road ingestion path rather than tapping their raw tables. Our benefits We’re a scaling start up, and we enjoy sharing our success, when the company succeeds, we always reinvest that in our people. We also offer huge amount