Position Management System Engineer

As Position Management System Engineer, you will own the firm's real-time system of record for what every client holds — the streaming platform where custodian files, order fills, and money movement converge into a single live view of holdings, transactions, and tax lots across every account. Your Impact Own and extend greenfield position engine — the materialized-view pipeline that turns an append-only ledger into normalized, cross-vendor positions that update as events land, not on a batch schedule Onboard start-of-day and intraday feeds from Schwab, Fidelity, Pershing, and portfolio-accounting platforms into the raw layer with full provenance Build the reconciliation layer: continuously prove computed positions against what the street reports, surface breaks immediately, and drive them to resolution Integrate pricing feeds — SIP/consolidated data or vendors like ICE, Refinitiv, or Polygon — so every record carries a market value marked to the latest print Own the security master: the instrument reference data (CUSIP/ISIN/FIGI identifiers, fixed-income terms, option contracts) everything else resolves against Run it in production — capacity planning, alerting, and incident response for a system the trading desk depends on The Ideal Match 5+ years building position management, portfolio accounting, or books-and-records systems at a broker-dealer, clearing firm, or RIA platform Fluent in cost-basis accounting and cancel/rebook semantics Thinks in incremental, event-driven computation — event-time semantics, at-least-once delivery, deduplication, checkpointing, and state management A builder's mindset — you'd rather own one critical system end-to-end than many shallow ones Technical Stack ECS Fargate, backed by an Aurora PostgreSQL metadata store and S3 object storage Python and SQL Event backbone of Lambda, SNS/SQS, and EventBridge Infrastructure-as-code (CDK), CodePipeline-driven CI/CD, and Parquet-based data-lake integration Bonus Points Corporate actions processing — splits, dividends, mergers — and their downstream effects Bitemporal or point-in-time modeling (as-of vs. as-known) Hands-on time with Materialize, Flink, or similar engines #J-18808-Ljbffr WSN