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SentiLink is a Series B fintech company providing identity verification and fraud detection solutions. The company has achieved significant traction, verifying hundreds of millions of identities through real-time APIs, with backing from top-tier investors including Andreessen Horowitz and Craft Ventures. SentiLink has been recognized by Forbes (Fintech 50), TechCrunch, CNBC, and Bloomberg, and was the first company to go live with eCBSV.
As a Staff Software Engineer on the Data Platform team, you will define the technical direction of the data infrastructure powering SentiLink's fraud detection and identity verification products. You'll own the design and evolution of critical systems that enable engineering, product, and data science teams to build reliable, scalable, high-performing solutions.
Key responsibilities include: defining long-term technical vision and architecture for the data platform; designing large-scale data infrastructure supporting identity and fraud detection at scale; leading architecture of secure, scalable batch and streaming pipelines processing billions of records; driving improvements in scalability, reliability, performance, observability, and operational excellence; partnering with Product, Engineering, Data Science, and Infrastructure teams on cross-functional technical challenges; establishing engineering standards and best practices across multiple teams; making build-versus-buy decisions and evaluating emerging technologies; improving production reliability and incident response; and developing deep expertise in identity, fraud detection, and large-scale data processing.
Required qualifications: 10+ years in software or data engineering with demonstrated ownership of large-scale distributed systems; expert-level proficiency in Python or Golang; extensive experience designing and operating large-scale ETL/ELT and streaming platforms (Spark, Kafka, Flink, Hadoop); strong experience with AWS, Azure, or GCP distributed systems; deep expertise across relational databases (PostgreSQL), search platforms (OpenSearch), columnar stores, object storage, and data lake architectures; experience with containerized services on Kubernetes; strong Infrastructure-as-Code, CI/CD, observability, and DevOps knowledge; demonstrated ability to lead technical initiatives across multiple teams; proven architectural decision-making balancing scalability, reliability, maintainability, and developer productivity; strong communication and cross-team influence skills; comfort operating in ambiguous environments while independently driving complex initiatives.
Bonus experience includes AWS services (EKS, SQS/SNS, EMR, Redshift, S3, Lambda, Glue), designing data platforms for ML/AI workloads, and prior experience at high-growth infrastructure or fintech companies.
