Lead the design, development, and support of party reference data applications and services.
Partner with architects and business stakeholders to implement data solutions supporting client, counterparty, issuer, and legal entity data domains.
Build and maintain cloud-native data pipelines utilizing AWS services including Glue, Lambda, EventBridge, S3, RDS, and Kafka/MSK.
Support modernization initiatives by migrating legacy reference data platforms to scalable cloud-based architectures.
Integrate and manage third-party reference data providers such as Dun & Bradstreet, S&P Global, and other enrichment sources.
Develop and maintain APIs and data services supporting compliance, CRM, operations, reporting, and trading systems.
Implement data quality controls, validation frameworks, deduplication processes, and lineage tracking capabilities.
Collaborate with data governance and architecture teams to support reference data standards and best practices.
Participate in Agile ceremonies, backlog refinement, estimation, and technical delivery planning using Jira.
Mentor junior engineers and provide technical guidance across project teams.
Support platform monitoring, resiliency, performance tuning, observability, and operational excellence initiatives.

Minimum of 7 years of experience in data engineering, software development, cloud engineering, or related fields.
Minimum of 2 years of experience leading projects, mentoring engineers, or serving as a technical lead.
Experience working with reference data, master data, customer data, legal entity data, or related domains.
Experience building and supporting cloud-native applications and data platforms.
Strong SQL and data modeling skills.
Experience developing APIs, data pipelines, and event-driven architectures.
Experience working in Agile delivery environments.

Lead Data Engineer

Key skills