Staff Software Engineer, Data Platform
$220k - $260kSentiLink
SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact with confidence. We’re building the future of identity verification in the United States replacing a clunky, ineffective, and expensive status quo with solutions that are 10x faster, smarter, and more accurate. We’ve seen tremendous traction and are growing extremely quickly. Our real-time APIs have helped verify hundreds of millions of identities, starting with financial services and rapidly expanding into new markets. SentiLink is backed by world-class investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin. We’ve earned recognition from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, American Banker, LendIt, and have been named to the Forbes Fintech 50. We have also been named a 2026 FICO Industry Vanguard Decision Award Winner. Last but not least, we’ve even made history - we were the first company to go live with the eCBSV and testified before the United States House of Representatives on the future of identity. SentiLink supports a variety of ways to work, ranging from fully remote to in-office. We operate as a digital-first company with strong collaboration across the U.S. and India. We maintain physical offices in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., and in Gurugram (Delhi) and Bengaluru in India. If you’re located near one of these offices, we would love for you to spend time in the office regularly. Some roles are hybrid or in-office by design. For example, our engineering team in India works primarily from our Gurugram office. Role: As a Staff Software Engineer on the Data Platform team at SentiLink, you will help define the technical direction of the data platform that powers our fraud detection products. You will own the design and evolution of critical data infrastructure, enabling engineering, product, and data science teams to build reliable, scalable, and high-performing systems. You'll partner closely with engineering leadership and cross-functional teams to solve some of the company's most complex technical challenges, balancing immediate product needs with long-term platform investments. As a technical leader, you'll influence architecture across multiple teams, mentor junior engineers on the team, and establish engineering standards that improve how we build and operate data systems. This is a remote, US-based role. Technologies: Python, Golang, PostgreSQL (RDS), OpenSearch, Redshift, EMR, Spark, Docker, Lambda, AWS technologies Responsibilities: Define the long-term technical vision and architecture for SentiLink's Data Platform. Design and evolve large-scale data infrastructure that powers our identity and fraud detection systems. Lead the architecture of secure, scalable, and highly reliable batch and streaming data pipelines capable of processing billions of records. Drive improvements in scalability, reliability, performance, observability, and operational excellence for the data platform. Partner with Product, Engineering, Data Science, and Infrastructure teams to solve cross-functional technical challenges and align platform investments with company priorities. Establish engineering standards, architectural patterns, and best practices for data infrastructure across multiple teams. Make thoughtful build-versus-buy decisions and evaluate emerging technologies to improve platform capabilities. Drive operational excellence by improving production reliability, incident response, and system observability. Participate in production support and on-call rotation while improving systems to reduce operational burden over time. Develop deep subject matter expertise in identity, fraud detection, and large-scale data processing. Requirements: 10+ years of experience in software engineering, data engineering, or a related field, 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 data platforms using technologies such as Spark, Kafka, Flink, Hadoop, or similar distributed processing frameworks. Strong experience designing scalable distributed systems in AWS, Azure, or GCP. Deep expertise across multiple data storage technologies, including relational databases (PostgreSQL), search platforms (OpenSearch), columnar data stores, object storage, and modern data lake architectures. Experience designing highly available, containerized services running on Kubernetes or similar orchestration platforms. Strong understanding of Infrastructure-as-Code, CI/CD, observability, and modern DevOps practices. Demonstrated ability to lead technical initiatives spanning multiple engineering teams. Proven experience making architectural decisions that balance scalability, reliability, maintainability, and developer productivity. Strong communication skills with the ability to influence technical direction across teams and levels. Comfortable operating in ambiguous environments while independently driving complex initiatives from concept to execution. Bonus Points: Experience with AWS technologies such as EKS, SQS/SNS, EMR, Redshift, S3, Lambda, and Glue. Experience designing data platforms supporting machine learning or AI workloads. Prior experience at a high-growth infrastructure, fintech, or data-intensive technology company. Compensation: $220,000 - $260,000 + equity + benefits Note: This salary range may be inclusive of multiple career levels, and the actual base salary within that range will be determined by several components including but not limited to the individual's experience, skills, and qualifications. Perks: Employer paid group health insurance for you and your dependents 401(k) plan with employer match (or equivalent for non US-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
$264k - $310k
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