Senior Lead Software Engineer, Risk Technology Data Platform & Strategy

What you'll do

• Lead the architecture and design of an enterprise-scale data platform using Databricks, AWS, and Lakehouse patterns.
• Deliver production-grade code for data ingestion, transformation, and serving pipelines across batch and streaming systems.
• Automate tenant onboarding, schema provisioning, and pipeline orchestration to enable self-service capabilities.
• Build infrastructure-as-code and CI/CD pipelines using Terraform while ensuring compliance with firm security policies.
• Integrate data governance, least-privilege access controls, and auditability into the core platform design.
• Define SLOs/SLAs and lead incident management and root-cause analysis to ensure platform resilience and observability.
• Evaluate new technologies and lead modernization efforts while balancing innovation with cost and operational readiness.
• Drive the adoption of AI-assisted engineering practices for code review, testing, and troubleshooting.

What we're looking for

• Formal training or certification on software engineering concepts and 5+ years of applied experience.
• Hands-on architecture and delivery of large-scale enterprise data platforms, including multi-tenant lakehouse or data mesh systems.
• Advanced proficiency in Python and/or Java (or Scala) and SQL within a regulated environment.
• Deep experience with Apache Spark, Databricks (including Unity Catalog), and open table formats like Delta Lake and Apache Iceberg.
• Experience with large-scale data ingestion, including CDC, event streaming (Kafka/Kinesis), and schema evolution.
• Practical cloud-native experience with AWS, infrastructure-as-code, and CI/CD in a policy-governed environment.
• Expertise in data governance, fine-grained access controls, data lineage, and handling sensitive data obligations.
• Proven technical leadership in driving architecture decisions, influencing senior stakeholders, and mentoring senior engineers.
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Mathematics, or a related technical field (preferred).
• Knowledge of financial services risk management data and regulatory reporting expectations (preferred).
• Experience building self-service data platform capabilities like automated onboarding and governed data sharing (preferred).