Data Platform Transformation Architect

Focus on this: • PYTHON TOO! • CI/CD, GitHub, version control and Terraform • Technical design (microservices, APIs, test strategy and front-end technologies) • Snowflake and database design • Extensive hands-on development • AI coding tools The role • Own the migration from legacy pipelines to a modern data platform that underpins how the entire firm interacts with data • Build trusted, well-modeled data layers across a complex multi-asset investment platform • Untangle existing business logic in stored procs and spreadsheets, re-implement in tested, version-controlled code • Reconcile data across multiple source systems and establish data quality standards • Make pragmatic data quality tradeoffs -- fix at source vs. patch downstream vs. document and move on • Maintain continuity of existing reporting through the transition Senior 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, Technical • Python, SQL, Snowflake, dbt, Airflow • Cloud data platforms (storage, orchestration, serverless) • Data modeling (dimensional, SCDs, snapshots) • Data quality tooling (great expectations, dbt tests, data contracts) • CI/CD for data pipelines • Stored procedure migration to modern ELT Domain (This is a plus but not required) • Investment data lifecycle: positions, transactions, prices, benchmarks, corporate actions, cash flows • Multi-asset: equities, fixed income, derivatives, alternatives • Previous experience with risk systems including Aladdin, Riskmetrics, Barra or equivalent preferred. • Portfolio analytics: returns, attribution, risk measures • Middle/back office systems (OMS, portfolio accounting, custodian feeds) • Financial data vendors (Bloomberg, MSCI, FactSet) • IBOR vs ABOR