Who you are

• You’re a streaming engineer with deep experience designing and implementing scalable, distributed data processing systems. You thrive in real-time environments where performance and reliability matter
• You’ve worked with Kafka (or similar) in production, understand the tradeoffs of event-driven architectures, and enjoy building resilient streaming pipelines that can handle massive throughput
• You’re comfortable collaborating with application engineers, product teams, and external vendors to translate requirements into well-architected, real-time data flows. You care about system design, monitoring, and data quality as much as raw throughput
• 5+ years of professional experience in data or software engineering, with at least 3 years focused on streaming/distributed systems
• Deep experience with Kafka (or similar streaming platforms such as Pulsar, Kinesis)
• Hands-on experience with Flink, Debezium, or other stream processing technologies
• Strong understanding of distributed systems concepts (scalability, partitioning, fault tolerance)
• Proficiency in at least one programming language such as Java, Scala, or Python (Ruby experience is a plus, or willingness to learn)
• Experience building and maintaining high-throughput streaming architectures in production
• Familiarity with data modeling and downstream analytics environments (Snowflake, BigQuery, Databricks) is a plus
• Solid understanding of data quality, validation, and monitoring techniques
• Excellent problem-solving skills, attention to detail, and communication abilities
• Be sure to mention “coffee” in your application so we know you actually read this

What the job involves

• Design and implement robust real-time data streaming pipelines using Kafka, Flink, Debezium, or Confluent
• Optimize streaming architectures for low-latency, high-throughput, and fault tolerance
• Build connectors and services to integrate vendor data streams (sensor data, telematics, fuel, accounting, etc.) into Fleetio’s platform
• Implement data validation, monitoring, and alerting strategies to ensure pipeline reliability and data quality
• Troubleshoot and resolve data processing issues in real time
• Document streaming architectures, data flows, and integration patterns
• Contribute to technical decision-making around Fleetio’s data streaming and integration strategy
• Collaborate with our Ruby on Rails application teams to ensure seamless integration between core platform features and streaming systems
• Support downstream batch/warehouse analytics when needed (Snowflake, ELT)

Benefits

• Health & Wellness: Taking care of you and your family is important to us. Our healthcare plans deliver choice and value so you can prioritize your health
• 401k Match: Plan for your future. We match your retirement contributions up to 4% of your salary each pay period
• PTO/Holidays: Four weeks of paid time off (PTO), two floating holidays, as well as 12 company holidays
• Parental Leave: We provide all our team members (birthing & non-birthday parents) time off to care for and bond with their newborn or newly adopted children
• Stock Options: At Fleetio, we grant all our team members options to acquire an ownership stake in Fleetio
• Professional Development: Team members get an annual professional development allowance to invest in their own professional growth