Lead Data Platform Engineer, Enablement & COE

About the Role:

A global financial institution is seeking a Lead Data Platform Engineer to help scale adoption of a strategic enterprise data platform. This role sits between core platform engineering, architecture, and business-aligned data teams, helping teams onboard successfully, adopt reusable frameworks, and follow consistent engineering standards.

This is not a heads-down development role. The right candidate will bring deep prior data engineering experience, strong Python/PySpark/SQL knowledge, and the ability to guide domain teams through platform setup, data onboarding, documentation, governance, quality controls, and framework adoption.

Responsibilities:

• Lead platform enablement and onboarding for data product and domain teams.
• Help teams understand intake steps, access needs, platform setup, and delivery standards.
• Drive adoption of reusable data engineering frameworks and common development patterns.
• Partner with architects, engineers, and stakeholders to translate requirements into clear platform needs.
• Support data quality, lineage, logging, metrics, auditability, and governance practices.
• Provide technical guidance, code review, and troubleshooting support where needed.
• Lead and coordinate a small group of engineers supporting COE and enablement work.
• Improve documentation, training, and operating models for platform adoption.

Role Requirements:

• 12+ years of experience in data engineering, cloud data platforms, data warehousing, or enterprise data architecture.
• Strong Python, PySpark, and SQL experience.
• Hands-on background with Databricks, Snowflake, or similar cloud data platforms.
• Experience with ETL/ELT, data pipelines, orchestration, data quality, and platform standards.
• Ability to review code, troubleshoot data engineering issues, and discuss technical tradeoffs.
• Experience supporting cross-team platform adoption, enablement, onboarding, or COE initiatives.
• Strong stakeholder management across business, technology, architecture, and engineering teams.
• Ability to lead or mentor engineers in a distributed team environment.
• Strong documentation, training, and communication skills.

Nice to Have:

• Financial services, banking, or regulated data environment experience.
• Experience with large-scale cloud data transformation or platform modernization.
• Exposure to data governance, lineage, auditability, and enterprise compliance requirements.
• Experience supporting globally distributed engineering teams.

How We Work:

• Hybrid NYC schedule, 5/10 days in office.
• Collaborative environment across platform, architecture, domain, and engineering teams.
• Strong focus on standards, reusable frameworks, and scalable delivery.
• Technical leadership role with stakeholder-facing responsibility.