2 months ago
Responsibilities
- Design, build, and maintain scalable data pipelines moving operational data from on-premises systems into cloud infrastructure.
- Architect and manage AWS infrastructure for scalable computation, data processing, and system telemetry.
- Integrate on-premises and cloud data flows into a cohesive and reliable data architecture.
- Build and maintain CI/CD pipelines supporting software delivery and validation across simulation and real-world testing environments.
- Implement and manage infrastructure-as-code with Terraform and CloudFormation.
- Develop internal services and automation tools for data ingestion, processing, and observability.
- Establish best practices for data reliability, pipeline observability, and system security.
- Lead root-cause analysis for data infrastructure and pipeline issues and design long-term resilience improvements.
- Collaborate with autonomy and systems engineers on scalable data interfaces and cloud deployment strategies.
Requirements
- Bachelor’s or master’s degree in Computer Science, Electrical Engineering, or a related field.
- 7+ years of experience building cloud infrastructure and data systems for large-scale distributed systems.
- Strong Python proficiency focused on data pipeline development and automation.
- Hands-on experience with Kafka, Kubernetes, and gRPC for scalable, high-throughput data systems.
- Deep expertise with AWS cloud services for compute, storage, and data processing.
- Experience with Jenkins, GitHub Actions, or CircleCI for CI/CD.
- Proficiency with Docker and Kubernetes for containerization and orchestration.
- Experience automating deployments with Terraform or CloudFormation.
- Familiarity with Git-based workflows, code review, and collaborative software development.
- Preferred experience integrating on-premises and cloud data flows in hybrid environments.
- Preferred background in data engineering for robotics, autonomous systems, or real-time operational data.
- Preferred knowledge of monitoring, logging, and alerting tools such as Prometheus, Grafana, or the ELK Stack.
- Preferred familiarity with networking, security, distributed-system performance optimization, and safety-critical, real-time, or high-availability systems.
Tech Stack
Categories
Data EngineeringDevOps
About AeroVect
AeroVect builds autonomous driving systems and software to automate airport ground service equipment, improving ramp logistics for airlines, airports, and ground handling providers. It deploys and supports autonomy for fleets used by major carriers and ground service companies. Founded in 2020 and headquartered in South San Francisco, it is a privately held Series A company.