Program Manager: Geospatial Data & AI Platform (Highways / Infrastructure)
About the Role
We are seeking a Program Manager to lead the delivery of a large-scale, cloud-native
geospatial analytics platform that ingests, processes, and analyzes road-condition and
dashcam data at national production scale. The platform combines full-stack applications,
GIS processing, computer-vision/ML models for road-defect detection, and a Databricks-
based lakehouse. The ideal candidate pairs strong program management discipline with
genuine technical uency across application, cloud infrastructure, data engineering, and
applied ML.
Key Responsibilities
Application Development & GIS

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Lead delivery of full-stack applications (JavaScript/React front end; containerized
backend APIs and worker services) for defect reporting, GIS visualization, and
analytics dashboards
Oversee API design and delivery across REST/HTTP APIs (API Gateway), event-driven
ingestion (Lambda, SQS, EventBridge), and caching/search layers
(Redis/ElastiCache, OpenSearch)
Coordinate GIS processing workstreams and map-based frontend delivery via CDN
(CloudFront)
Cloud Infrastructure (AWS)
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Own infrastructure provisioning across environments in AWS (ap-south-1 / Mumbai),
including ECS-on-EC2 compute, Aurora PostgreSQL (Multi-AZ), DynamoDB, VPC
networking (NAT, VPC endpoints, ALB), and bastion/admin access
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Drive environment separation, tagging, and shared-vs-dedicated service strategy
across production and staging (common Databricks/governance layers vs.
environment-isolated data and namespaces)
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Govern security, encryption, and compliance baselines: KMS/CMKs, Secrets
Manager, GuardDuty, AWS Cong, AWS Backup, Route 53/ACM
Manage cost, capacity, and scaling decisions (e.g., autoscaling compute, lifecycle
policies to S3-IA/Glacier for petabyte-scale raw archive)
Data Engineering & Warehouse (Databricks + AWS)

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Lead the lakehouse build-out on Databricks (SQL/Jobs/Photon compute, Workows
orchestration) with a node-scaling model tied to data volume growth
Oversee ETL/ingestion pipelines (AWS Glue, optional MWAA/Airow) and ad-hoc
analytics on the S3 data lake (Athena, Parquet/ORC)
Establish data governance and lineage across Lake Formation and Databricks Unity
Catalog, with separate catalogs/schemas per environment
Manage the evaluation of a curated warehouse path (Redshift Serverless/RA3)
alongside or instead of Databricks
Data Science & AI/ML
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Manage development and deployment of computer-vision and predictive models for
road-defect scoring and dashcam analytics (SageMaker real-time and batch
inference; GPU training on EC2 g4dn / SageMaker p3)
Oversee the model validation pipeline, including SageMaker Ground Truth labeling
workows (auto-label + human audit) across multi-vendor dashcam eets the
platform's largest cost driver, requiring tight scope, sampling, and budget control
Coordinate descriptive-analytics and algorithm work (e.g., deduplication and
coverage-gap analysis)
Required Qualications
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8+ years of program/project management in technology-driven, data-intensive
environments
Proven delivery of full-stack applications (JavaScript, React, containerized
backends)
Hands-on experience provisioning and governing AWS infrastructure (EC2/ECS,
RDS/Aurora, VPC networking, IAM/KMS, S3 at scale)
Experience overseeing AI/ML model development and deployment, ideally
computer vision, on SageMaker or equivalent
Experience with lakehouse/data-warehouse platforms,



specically Databricks (and
familiarity with Redshift, Glue, Athena)
Demonstrated ability to manage multi-environment delivery with cost, security, and
governance discipline

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Strong stakeholder management and cross-functional leadership; Agile/Scrum
familiarity
Stakeholder & Team Management
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Coordinate delivery across the application team (front-end, backend), data
engineering team (lakehouse, ETL, warehouse), and data science team
(CV/predictive modeling), sequencing cross-team dependencies so pipelines and
labeled data are ready when models need them, and model outputs/APIs are
production-ready when the app team integrates them
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Manage upward and outward to client and public-sector sponsors (e.g.,
client/program leadership), infrastructure and security/compliance reviewers, and
external vendors (dashcam eet and labeling providers)
Translate technical trade-os into transparent scope, cost, and timeline decisions,
maintaining a shared view of progress, risks, and priorities across all parties
Preferred Qualications
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Bachelor's/Master's in Computer Science, Engineering, Data Science, or GIS
PMP, CSM, or AWS certication (e.g., Solutions Architect)
Prior hands-on background as a developer, data engineer, or data scientist
Experience with geospatial/GIS platforms or public-sector / infrastructure programs
Experience managing large data-volume programs (multi-petabyte) and associated
cloud cost optimization
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Vendor and budget management across managed-labeling or eld-data-collection
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What You'll Bring
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Fluency translating across application, cloud, data-engineering, and ML teams
Comfort operating from front-end through petabyte-scale data and applied ML
A delivery and cost-focused mindset with strong risk management, especially where
a single workstream (e.g., ML validation/labeling) dominates program spend

📌 Program Manager: Geospatial Data & AI Platform (Gurugram)
🏢 Indypay Technologies
📍 Gurugram