Engineering Manager, Data Platform

Engineering Manager – Data Platform Responsible for building and scaling the data infrastructure that powers SentiLink’s products and decisioning systems. This remote U.S.-based role leads a team of data engineers and partners closely with Data Science, Product, and Engineering to ensure reliable, actionable data across the company. Technologies Golang, Python PostgreSQL (RDS), Redshift, EMR, Spark Docker, OpenSearch, AWS (Lambda, Cognito, other services) Responsibilities Lead and grow a team of data engineers responsible for the data platform and infrastructure Define and drive the technical vision for data ingestion, processing, storage, and serving systems Design and evolve scalable data pipelines (batch and real‑time) to support product and data science use cases Ensure high standards for data quality, reliability, and observability across all data systems Partner with Data Science to enable pipelines and efficient access to high-quality data Collaborate with Product and Engineering to power data‑driven features and decisioning systems Work closely with Infrastructure to optimize performance, cost, and scalability of data systems Establish best practices for data governance, schema management, and pipeline reliability Support operational excellence, including monitoring, alerting, and incident response for data systems Hire, mentor, and develop engineers while maintaining a high hiring bar Foster a culture of ownership, accountability, and continuous improvement Contribute to architecture and technical problem‑solving as needed Requirements 2‑5+ years of engineering management experience leading data or platform teams Strong background as a senior or staff‑level data engineer or backend engineer with data focus Experience building and scaling data platforms, including ETL/ELT pipelines and data infrastructure Proficiency in Python, Golang, or similar languages Deep understanding of distributed data systems, batch and streaming architectures Experience with cloud‑based data platforms (AWS, GCP, or Azure) Strong knowledge of databases, data modeling, and query optimization (SQL, RDBMS, data warehouses) Track record of delivering reliable, scalable data systems in production environments Comfortable leading technical discussions and diving into system design details Experience operating in fast‑paced, startup or growth‑stage environments Experience with big data and streaming technologies (Spark, Kafka, Flink, etc.) preferred Familiarity with data lakes, warehouses (Redshift), and modern data architectures preferred Experience building data platforms that support ML or fraud/risk systems preferred Fintech or fraud domain experience preferred Compensation $200,000/year - $240,000/year + equity + benefits Perks Employer‑paid group health insurance for you and your dependents 401(k) plan with employer match (or equivalent for non‑U.S.–based roles) Flexible paid time off Regular company‑wide in‑person events Home office stipend, and more! Corporate Values Follow Through Deep Understanding Whatever It Takes Do Something Smart #J-18808-Ljbffr