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Strong employer brand and metro location increase competition for this senior data engineering manager role.
Requires domain-specific data engineering and financial/document processing expertise, reducing cross-industry transferability.
Explicit 8+ years, leadership expectation, and specific data engineering tech stack make screening stringent.
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Lead a team of 5-8 engineers in building scalable, automated data engineering platforms for processing large volumes of financial data and documents.
Own architecture, design, and delivery of cloud-native, event-driven, AI-assisted data pipelines with focus on efficiency, scalability, and automation.
Collaborate with Product, Architecture, and Engineering leadership to translate complex business problems into scalable technical solutions and drive execution excellence.
8+ years software engineering experience with strong data engineering expertise.
Prior experience leading engineering teams in a product organization.
Proficiency with Python, Pandas, NumPy, PyArrow, FastAPI, PostgreSQL, DynamoDB, Redis, Elasticsearch, AWS services, Docker/containerized deployments.
Bachelor's degree in Engineering, Computer Science, or equivalent.
Experienced in architecting and scaling large backend systems and high-volume data processing pipelines in financial or related domains.
Strong technical leadership combining hands-on architecture and coding with engineering management and execution.
Skilled in driving automation-first practices, delivering cloud-native solutions on AWS, and collaborating across multiple teams for technical alignment and impact.