Staff Software Engineer, Data Platform
New
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SentiLinkFintech / Identity
United StatesFull-TimeStaff
Salary$220,000 - $260,000 + equity + benefits
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Job Details
- Experience
- 10+ years
- Required Skills
- AWSPostgreSQLPythonKafkaKubernetesGoSparkDevOps
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.
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.
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