Engineering Manager - Cloud and Data Analytics

Job Description

Must-Have: Bachelors or Masters in Computer Science, Electrical Engineering, or related field. 7+ years of experience in software/product engineering, with 2+ years in a technical leadership or management role. Deep understanding of cloud architecture, video pipelines, edge computing, and microservices. Proficient in AWS/GCP/Azure, Docker/Kubernetes, serverless computing, and RESTful API design. Solid grasp of AI/ML integration and computer vision workflows (model lifecycle, optimization, deployment). Experience in data pipelines, SQL/NoSQL databases, and analytics tools (e.g., Redshift, Snowflake, Grafana, Superset). Good-to-Have: Prior work on automotive, fleet, or video telematics solutions. Experience with camera hardware (MIPI, ISP tuning), compression codecs (H.264/H.265), and event-based recording. Familiarity with telematics protocols (CAN, MQTT) and geospatial analytics. Working knowledge of data privacy regulations (GDPR, CCPA). Key Responsibilities: Platform Leadership Own and drive the development of the complete video telematics ecosystem, covering edge AI, video processing, cloud platform, and data insights. Architect and oversee scalable and secure cloud infrastructure for video streaming, data storage, OTA updates, analytics, and alerting systems. Define the data pipeline architecture for collecting, storing, analyzing, and visualizing video, sensor, and telematics data. Cross-functional Engineering Management Lead and coordinate cross-functional teams: Cloud/backend team for infrastructure, APIs, analytics dashboards, and system scalability. AI/ML and CV teams for DMS/ADAS model deployment and real-time inference. Hardware/Embedded teams for firmware integration, camera tuning, and SoC optimization. Collaborate with product and business stakeholders to define the roadmap, features, and timelines. Data Analytics Work closely with data scientists to build meaningful insights and reports from video and sensor data. Drive implementation of real-time analytics, fleet safety scoring, and predictive insights using telematics data. Operational Responsibilities Own product quality and system reliability across all components. Support product rollout, monitoring, and updates in production. Manage resources, mentor engineers, and build a high-performing development team. Ensure adherence to industry standards for security, privacy (GDPR), and compliance (e.g., GSR, AIS-140).