Lead and grow a team of data engineers responsible for SentiLink’s 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 their pipelines and enable efficient access to high-quality data
Collaborate with Product and Engineering teams 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

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.

Engineering Manager, Data Platform

Key skills