Location :: Denver, CO(3 days a week- Hybrid)
Type :: Contract
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
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