Job Title: Full Stack Data Platform Engineer

Location:
Bangalore, India

Experience:
5
- 8+ Years Function: Technology | Data Platform Engineering | Cloud & AI Platforms Mode: Initially 2 weeks hybrid then work from home Compensation: Raise as per the market on the current compensation. Maximum up to INR 24lpa Primary skills
- Full stack (React, NodeJs, CI/CD, etc.) Secondary skills
- Data engineering (including some exposure to Snowflake, Databricks or similar data platform), AI/Agentic The resources are expected to build service layer that could be used by Data Engineers Role Summary Client is seeking a highly experienced Platform Engineer to design, build, and operate enterprise-grade Data & AI Platform capabilities supporting Analytics, AI, Generative AI, and Agentic AI workloads. The role is focused on modernizing platform capabilities that enable scalable, governed, and self-service data consumption while supporting AI-driven decision-making and autonomous workflow. The successful candidate will contribute to Data Engineering as a Service, Self-Service Analytics, Semantic Layers, Intelligent Data Products, and AI-ready architecture. This is a hands-on engineering role requiring expertise in AWS Cloud, Platform Engineering, Full Stack Development, Microservices Architecture, DevOps, and modern software engineering practices.

Key Responsibilities
Data & AI Platform Engineering
• Design, develop, and enhance enterprise Data & AI Platform capabilities supporting analytics, AI, Agentic AI, and modern data platform use cases.
• Build platform capabilities enabling Data Engineering as a Service, Data Quality as a Service, Data Discovery, Governance, and standardized data consumption.
• Develop Semantic Layer and Self-Service Analytics capabilities for business users, analysts, and AI applications.
• Enable trusted and governed data access across enterprise platforms.
• Support intelligent data products and AI-ready platform architectures. Application & Platform Development
• Build cloud-native applications, APIs, platform services, automation frameworks, and developer productivity tools.
• Develop reusable platform services, accelerators, SDKs, and engineering frameworks.
• Design capabilities supporting data ingestion, transformation, orchestration, observability, and platform operations.
• Build scalable and resilient enterprise applications using modern software engineering patterns. Cloud & Platform Operations
• Develop secure, scalable, and resilient AWS-based platform solutions.
• Implement CI/CD, Infrastructure as Code, DevOps automation, and cloud-native operational frameworks.




• Contribute to platform reliability, cloud cost optimization, performance tuning, incident management, and operational excellence initiatives.
• Support enterprise security, privacy, governance, and compliance requirements. Data Governance & Enablement
• Contribute to metadata management, lineage, data quality, observability, governance, and compliance initiatives.
• Support semantic retrieval and integration capabilities for AI-driven workloads.
• Enable enterprise-wide self-service analytics and trusted data consumption frameworks.
• Drive enterprise data enablement through modern governance and metadata practices. AI & Innovation
• Support AI-ready platform architecture and emerging AI technologies.
• Enable integrations supporting Agentic AI, Generative AI, intelligent automation, and orchestration platforms.
• Collaborate with data scientists and AI teams to build scalable AI-enablement capabilities.
• Contribute to modern AI engineering and emerging technology initiatives. Stakeholder Collaboration
• Work closely with Data Engineers, Data Scientists, Platform Engineers, Architects, and business stakeholders.
• Deliver reusable services and platform capabilities that accelerate adoption and innovation.
• Translate business needs into scalable engineering solutions.
• Drive collaboration across business and technology teams. Primary Skills (Must Have) Platform Engineering & Cloud
• AWS Cloud Platform
• ECS / EKS
• AWS Lambda
• API Gateway
• S3
• IAM
• VPC
• CloudWatch
• Secrets Manager
• Route 53
• Enterprise Platform Engineering
• Internal Developer Platforms
• Cloud Security & Governance
• Distributed Systems Architecture Software Engineering
• React
• TypeScript
• JavaScript
• Node.js
• REST APIs
• GraphQL APIs
• Microservices Architecture
• Domain Driven Design (DDD)
• API First Development
• Service-Oriented Architecture
• Secure Coding Practices
• Testing Frameworks (Unit, Integration, Contract & End-to-End Testing) DevOps & Automation
• CI/CD Pipelines
• Infrastructure as Code (Terraform, CloudFormation, CDK)
• Git
• Docker
• Kubernetes
• Platform Monitoring & Observability




• Logging & Operational Tooling
• DevOps Practices Data & Analytics Platforms
• Snowflake
• Databricks
• AWS Data Services
• Kafka
• Data Warehousing
• Lakehouse Architecture
• Data Mesh
• Data Fabric
• Medallion Architecture
• Data Products
• Semantic Layers
• Self-Service Analytics
• Data Governance
• Data Quality
• Metadata Management
• Data Lineage Secondary Skills (Nice to Have) AI & Emerging Technology
• Generative AI
• Agentic AI
• AI Engineering Practices
• LLM Integrations
• Vector Databases
• MCP Servers
• AI Orchestration Frameworks
• AI Governance
• Azure AI
• OpenAI
• Amazon Bedrock
• Snowflake Cortex Additional Desirable Skills
• MLOps
• AI Platform Engineering
• Model Serving Platforms
• Event Driven Architectures
• Streaming Platforms
• Multi-Cloud Environments
• Airflow
• Astronomer
• Apache Spark
• Databricks
• GraphQL
• API Gateways
• Internal Developer Platforms
• Retail & eCommerce Industry Experience Key Competencies
• Strong Platform Engineering mindset.
• Expertise in scalable enterprise-grade platform development.
• Strong understanding of Data Products and Semantic Layers.
• Knowledge of Data Governance and AI Governance frameworks.
• Focus on automation, standardization, and platform innovation.
• Solid analytical and problem-solving skills.
• Ability to operate in rapidly evolving cloud and AI environments.
• Excellent communication and stakeholder management capabilities.
• Ability to translate business requirements into scalable technical solutions. Experience & Qualifications Education
• Bachelor's Degree in Engineering (Mandatory)
• Master's Degree in Computer Science or IT (Preferred) Experience
• 5-8 years of relevant experience.
• Hands-on experience building and operating enterprise-grade production platforms.
• Strong experience implementing cloud-native architectures and distributed systems.
• Proven expertise with AWS platform development.
• Experience building scalable Full Stack applications using React, TypeScript/JavaScript, and Node.js.
• Experience supporting Data & AI platform modernization programs.
• Experience implementing modern development practices including Agile, DevOps, Git, CI/CD, IaC, and automated testing.
• Experience supporting reliability, observability, governance, security, and cloud cost optimization initiatives.
• Retail, eCommerce, or customer-facing digital platform experience is highly preferred.

📌 Full Stack Data Platform Engineer (Bengaluru)
🏢 Vriba Solutions
📍 Bengaluru