INRIX aggregates connected-vehicle and device data into traffic and mobility insights for cities, logistics, and financial services. The tech stack is heavily weighted toward AWS data infrastructure (Glue, Athena, EMR, Kinesis, RDS) paired with distributed compute (Spark, Hadoop, MapReduce), reflecting the scale required to process large-time-series transportation datasets. Current hiring skews sales (4 roles) over engineering (2), signaling a push to expand market coverage for their analytics platform rather than major product re-architecture.
Tech Stack 36 technologies
Core StackSalesforce ZoomInfo Salesloft Python Postman AWS AWS Glue Java Apache Spark Kafka Hadoop Scala AWS RDS AWS Lambda Jenkins Terraform LinkedIn Sales Navigator QGIS AWS Athena AWS EMR Amazon Athena Amazon EMR MapReduce PostGIS AWS Kinesis AWS ElastiCache AWS ECS AWS CloudWatch AWS Elastic Beanstalk Azure Entra ID+6 more
What INRIX Is Building
◆Challenges
- Reducing recurring operational overhead
- Maintaining secure core systems
- Transform massive traffic data
- Real-time traffic insights
- Large-scale traffic datasets
- Static demographics
- Outdated traffic counts
- High‑stakes site selection
- Reducing congestion
- Improving safety
▲Active Projects
- Automating manual processes with powershell and apis
- Infrastructure automation with terraform
- Ci/cd workflow improvement with github actions
- Next generation real-time transportation applications
- Real-time traffic insights platform
- Data pipelines for traffic data
- Site selection and expansion
- Portfolio optimization
- Store performance evaluation
Hiring Activity
9 roles · 8 in 30d
Department
Seniority
Company intelligence
