Forward Deploy Sr. Data Engineer-VP

About this role About the Role BlackRock's Enterprise Data Platform (EDP) is the firm's strategic foundation for how data products are built, governed, and consumed at scale, powering investment decisions, risk analytics, and operational workflows across the firm and its global client base. Data Platform as a Service (DPaaS) is a core capability within EDP, purpose-built to make data product creation fast, reliable, and repeatable. Whether a team is onboarding a new market data feed, publishing a risk dataset, or operationalizing a model output, DPaaS provides the infrastructure, tooling, and guided experience to take a raw data source and turn it into a trusted, production-grade data product. Teams get acquisition, ingestion, transformation, quality validation, and governance without having to build any of it themselves. Why This Role is Exciting Most engineers either build platforms or use them. As a Forward Deploy Engineer on the DPaaS team, you do both. You will deploy by embedding directly with teams across the firm, bringing their data products to life and solving real problems that only surface when a platform meets production data. You will build by developing solutions that fill gaps and make it easier for teams to create and publish data products on EDP. You will be at the frontier of how BlackRock thinks about data products, working with real users, influencing what gets built next, and seeing your work in production quickly across a wide range of data domains. What You Will Do Forward Deployment & Data Product Onboarding Embed directly with partner engineering and data teams to drive end-to-end data product onboarding onto DPaaS, from source configuration through to production Work hands-on with teams to define data product structure including schema, ownership, SLAs, quality expectations, and governance attributes Support onboarding of both structured and unstructured data products, adapting approaches to fit the nature of the data Troubleshoot onboarding failures across infrastructure, pipeline, and data layers in real time Run technical onboarding sessions and workshops tailored to each team's data product needs Enable partner teams to self-serve on data product creation over time, reducing dependency on FDE support Solution Development & Platform Contribution Develop reusable data product accelerators including pipeline templates, configuration generators, and schema mapping utilities Build custom acquisition connectors, ingestion templates, and transformation scaffolding for both structured and unstructured data Contribute to core DPaaS platform engineering efforts including new feature development and framework improvements Build and maintain data product accelerators and onboarding utilities that become reusable assets across the platform Client Enablement Act as a trusted technical advisor on data product design and onboarding best practices for partner engineering and data teams Run office hours, enablement sessions, and targeted training to help teams build platform confidence independently Translate partner-specific data requirements into platform-compatible data product configurations Document onboarding patterns, common failure modes, and solutions into reusable playbooks Capture and channel structured feedback from onboarding engagements into the DPaaS product and engineering roadmap AI Assisted Development & Intelligent Data Product Onboarding Use AI assisted coding tools as a core part of daily workflow, accelerating configuration authoring, pipeline generation, and onboarding automation Build and contribute to AI assisted onboarding workflows leveraging schema inference, automated attribute mapping, and AI driven data profiling to reduce manual effort Implement emerging AI tooling including Model Context Protocol (MCP), AI agents, and Copilot extensions to automate repetitive onboarding tasks Define what AI native data product creation looks like on EDP, contributing ... (truncated, view full listing at source)