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
- 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.