Engineering Manager- Aftermarket (Cloud and Data Analytics)
A top industrial automation company which is part of a top engineering group
5 - 10 years
Gurugram
Posted: 24/12/2025
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Job Description
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).
Pre-Requisites:
- 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).
- 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)
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