Senior Data Engineer, Compliance Data Infrastructure

Design, build, and maintain scalable data pipelines for compliance analytics use cases such as AML monitoring, KYC/KYB, and SAR reporting, while assessing and improving existing infrastructure to resolve data quality and lineage issues. This role involves partnering with data scientists to productionize feature pipelines, implementing robust data quality monitoring, and ensuring infrastructure meets regulatory requirements for data retention and auditability. Candidates must have 8+ years in data engineering, preferably with experience in financial services or compliance, demonstrating strong proficiency in Python, SQL, and distributed computing frameworks like Spark. Essential requirements include hands-on fluency with AI-assisted engineering using LLM tools and experience designing data marts/semantic layers, alongside a solid grounding in data governance for regulated industries.