Director - Enterprise Data Platform

About this role About the Team: You will be joining a newly launched Forward Deployed Engineering team dedicated to client engagement and platform adoption. This team operates with a startup mentality within the company – high collaboration, agility, and a focus on delivering results. As a principal FDE, you’ll serve as a key leader in this team, helping establish its practices and culture. You’ll work alongside seasoned data platform engineers and product managers, directly contributing to our mission of empowering users to unlock maximum value from data. Job Summary: We are seeking a Principal-level Forward Deployed Engineer (FDE) Lead to spearhead client-facing technical engagements for our Enterprise Data Platform (EDP). In this high-impact individual contributor role, you will bring product-grade data engineering expertise directly to internal (and later external) clients to drive adoption of our EDP. This role is not primarily a pipeline engineering role. Instead, you will act as a technical authority, advisor, and enablement lead—working with our Data Platform as a Service (DPaaS) adopters to design high-quality data pipelines, teach best practices, and guide teams to build and operate pipelines effectively themselves. You will help clients understand  how  to build pipelines well on EDP, review designs and implementations, and unblock complex issues, while leaving daytoday pipeline construction and ownership with the adopting teams. This role combines deep hands-on technical work (in Airflow, Snowflake, dbt, Great Expectations, DataHub, etc.) with strategic advisory responsibilities. As a founding member of the Forward Deployed Engineering team, you will play a pivotal role in shaping how we accelerate data platform adoption and deliver insights in the investment management domain. The position is remote-friendly with minimal travel (occasional client visits if needed). Key Responsibilities: Direct Client Engagement & Solution Delivery: Serve as a trusted technical advisor for DPaaS adopters, partnering with teams to understand their business goals and data needs. Guide clients in designing EDP-native data pipelines, helping them select appropriate patterns, architectures, and platform features. Enable teams to become self-sufficient and effective builders by transferring knowledge, patterns, and best practices rather than owning pipeline delivery. Data Pipeline Design & Best Practices: Provide expert guidance on EDP data pipeline design, including ingestion, transformation, orchestration, and consumption patterns. Advise on Airflow DAG design, dbt project structure, dependency management, and operational best practices—without routinely building or owning pipelines yourself. Help teams adopt scalable, maintainable approaches aligned to medallion (bronze–silver–gold) architectures, data mesh principles, and EDP standards. Snowflake Architecture & Optimization Guidance: Act as a Snowflake subject-matter expert, advising teams on data modeling, SQL design, warehouse sizing, and performance optimization. Review and provide feedback on query patterns, schema designs, and workload configurations to help adopters achieve cost-efficient, performant solutions. Support teams in diagnosing performance or cost issues, guiding them toward effective remediation. Design Review, Quality & Governance: Review pipeline designs, data models, and implementation approaches to ensure alignment with enterprise data quality, governance, and security standards. Coach teams on implementing data quality checks using Great Expectations and on improving metadata, lineage, and discoverability via DataHub or similar tools. Promote consistent engineering standards, documentation practices, and operational readiness. Data Quality & Governance: Implement and promote best practices in data quality, validation, and governance. Utilize Great Expectations for automated data quality checks and DataHub (or similar metadata/catalog tools) to impro ... (truncated, view full listing at source)