Data Platform Transformation Architect

Focus on this:PYTHON TOO!CI/CD, GitHub, version control and TerraformTechnical design (microservices, APIs, test strategy and front-end technologies)Snowflake and database designExtensive hands-on developmentAI coding toolsThe roleOwn the migration from legacy pipelines to a modern data platform that underpins how the entire firm interacts with dataBuild trusted, well-modeled data layers across a complex multi-asset investment platformUntangle existing business logic in stored procs and spreadsheets, re-implement in tested, version-controlled codeReconcile data across multiple source systems and establish data quality standardsMake pragmatic data quality tradeoffs -- fix at source vs. patch downstream vs. document and move onMaintain continuity of existing reporting through the transitionSenior data/analytics engineer who has led a data platform transformation . Has worked in environments with complex legacy systems and multiple data sources -- and knows how to modernize them without breaking what's already running. 7-10+ years in data engineering,TechnicalPython, SQL, Snowflake, dbt, AirflowCloud data platforms (storage, orchestration, serverless)Data modeling (dimensional, SCDs, snapshots)Data quality tooling (great expectations, dbt tests, data contracts)CI/CD for data pipelinesStored procedure migration to modern ELTDomain (This is a plus but not required)Investment data lifecycle: positions, transactions, prices, benchmarks, corporate actions, cash flowsMulti-asset: equities, fixed income, derivatives, alternativesPrevious experience with risk systems including Aladdin, Riskmetrics, Barra or equivalent preferred.Portfolio analytics: returns, attribution, risk measuresMiddle/back office systems (OMS, portfolio accounting, custodian feeds)Financial data vendors (Bloomberg, MSCI, FactSet)IBOR vs ABOR