Platform Engineer

Vriba Solutions; Bengaluru; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Vriba Solutions in Bengaluru, India, is seeking a highly experienced Engineer, Data Platform to design, build, and operate enterprise-grade platform capabilities supporting Data, Analytics, AI, and Agentic AI workloads. You will help modernize the Data & AI Platform with scalable, governed, self-service, and AI-ready data capabilities across the enterprise.

The role focuses on Data Engineering as a Service, self-service analytics, semantic layer capabilities, intelligent data products, and

Qualifications

• Bachelor's Degree in Engineering or related discipline.
• Master's Degree in Computer Science, Information Technology, or related field.
• Proven experience building and operating production-grade enterprise platforms.
• Strong expertise in designing and implementing cloud-native architectures, APIs, microservices, and distributed systems.

Responsibilities

• Design, build, and operate enterprise Data & AI Platform capabilities supporting analytics, AI, Agentic AI, and modern data platform use cases.
• Build platform capabilities that enable Data Engineering as a Service, Data Quality as a Service, data discovery, governance, and standardized data consumption patterns
• Develop semantic layer and self-service analytics capabilities to provide business users, analysts, and AI applications with trusted and governed data access
• Build cloud-native applications, APIs, platform services, automation frameworks, and developer tools to improve productivity across Data Engineering, Analytics, AI, and business teams
• Design and implement reusable platform services, accelerators, SDKs, and engineering frameworks for data ingestion, transformation, orchestration, observability, and platform operations
• Develop secure, scalable, and resilient platform solutions on AWS using microservices, CI/CD, Infrastructure as Code (IaC), automation, and DevOps practices.
• Support data quality, metadata management, lineage, observability, governance, security, privacy, and compliance initiatives
• Enable AI-ready platform architecture through data, metadata, orchestration, semantic retrieval, and integration capabilities required for Agentic AI and intelligent automation.
• Collaborate with Data Engineers, Data Scientists, Platform Engineers, Architects, and business stakeholders to deliver scalable platform capabilities.
• Contribute to platform reliability, performance optimization, operational excellence, incident management, and cloud cost optimization activities.

Skills

AWS Cloud

Cloud-Native Architectures

Cloud Security & Networking

Scalability & Reliability Engineering

Full Stack Development

React

Node.js

API Development

Testing Frameworks

Git

Infrastructure as Code

Containerization

Automation Frameworks

Monitoring & Observability

Logging & Operational Excellence

Snowflake

Kafka

Data Warehousing

Data Governance

Data Quality Management

Semantic Layer Architecture

Agentic AI

Retrieval-Augmented Generation

Internal Developer Platforms

Streaming Platforms

Data Cataloging

Multi-Cloud Environments

MLOps

Model Serving

Astronomer

Databricks

Education

Bachelor's Degree in Engineering or related discipline

Master's Degree in Computer Science, Information Technology, or related field

Tools

Snowflake

Databricks

Kafka

Astronomer

Job description

Function: Technology

Experience: 5-8 Years

Data Platform Engg:

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 Engineer, Data Platform to design, build, and operate enterprise-grade platform capabilities supporting Data, Analytics, AI, and Agentic AI workloads. The role will be instrumental in modernizing the organization's Data & AI Platform by enabling scalable, governed, self-service, and AI-ready data capabilities across the enterprise

The successful candidate will contribute to the development of Data Engineering as a Service, Self-Service Analytics, Semantic Layer capabilities, Intelligent Data Products, and Agentic AI enablement. This is a hands-on engineering role requiring strong expertise in AWS cloud technologies, Full Stack Development, Platform Engineering, Microservices Architecture, and modern software development practices.

Key Responsibilities

• Design, develop, and enhance enterprise Data & AI Platform capabilities supporting analytics, AI, Agentic AI, and modern data platform use cases.
• Build platform capabilities that enable Data Engineering as a Service, Data Quality as a Service, data discovery, governance, and standardized data consumption patterns
• Develop semantic layer and self-service analytics capabilities to provide business users, analysts, and AI applications with trusted and governed data access
• Build cloud-native applications, APIs, platform services, automation frameworks, and developer tools to improve productivity across Data Engineering, Analytics, AI, and business teams
• Design and implement reusable platform services, accelerators, SDKs, and engineering frameworks for data ingestion, transformation, orchestration, observability, and platform operations
• Develop secure, scalable, and resilient platform solutions on AWS using microservices, CI/CD, Infrastructure as Code (IaC), automation, and DevOps practices.
• Support data quality, metadata management, lineage, observability, governance, security, privacy, and compliance initiatives
• Enable AI-ready platform architecture through data, metadata, orchestration, semantic retrieval, and integration capabilities required for Agentic AI and intelligent automation.
• Collaborate with Data Engineers, Data Scientists, Platform Engineers, Architects, and business stakeholders to deliver scalable platform capabilities.
• Contribute to platform reliability, performance optimization, operational excellence, incident management, and cloud cost optimization activities.

Primary Skills (Must Have)

• AWS Cloud
• Cloud-Native Architectures
• Cloud Security & Networking
• Scalability & Reliability Engineering

Software Engineering

• Full Stack Development
• React
• Node.js
• API Development
• Testing Frameworks

DevOps & Automation

• Git
• Infrastructure as Code (IaC)
• Containerization
• Automation FrameworksMonitoring & Observability
• Logging & Operational Excellence

Data & AI Platforms

• Snowflake
• Kafka
• Data Warehousing
• Data Governance
• Data Quality Management
• Semantic Layer Architecture
• Agentic AI
• Retrieval-Augmented Generation (RAG)

Advanced Platform & Data Engineering

• Internal Developer Platforms
• Streaming Platforms
• Data Cataloging
• Multi-Cloud Environments
• MLOps
• Model Serving
• Astronomer
• Databricks

Domain Experience

• Retail
• eCommerce
• Supply Chain
• Customer-Facing Digital Platforms
• Strong focus on building scalable, reusable, enterprise-grade Data & AI platform capabilities.
• Strong understanding of data products, semantic layers, data governance, AI governance, and enterprise data enablement.
• Passion for delivering secure, trusted, and high-quality data products supporting analytics and AI.
• Strong engineering mindset focused on automation, standardization, and platform innovation.
• Adaptability to evolving Data, AI, Agentic AI, and cloud technologies.
• Excellent stakeholder management and collaboration skills with the ability to translate business requirements into technology solutions.
• Strong analytical and problem-solving capabilities.

Experience & Qualifications

Education

Required

• Bachelor's Degree in Engineering or related discipline.

Preferred

• Master's Degree in Computer Science, Information Technology, or related field.

Experience

• Proven experience building and operating production-grade enterprise platforms and business-critical applications.
• Strong expertise in designing and implementing cloud-native architectures, APIs, microservices, and distributed systems.
• Experience building and operating solutions on AWS.
• Experience supporting Data & AI Platform modernization initiatives.
• Experience building reusable platform services, APIs, automation capabilities, and developer tools.
• Strong understanding of platform security, identity management, governance, privacy, and compliance.
• Experience implementing Git, CI/CD, Infrastructure as Code, automated testing, Agile delivery, and DevOps practices.
• Experience supporting observability, reliability, performance optimization, and cloud cost management.
• Retail, eCommerce, or large-scale customer-facing digital platform experience preferred.

Ways of Working

• Hands-on contributor responsible for designing, building, and operating platform capabilities.
• Collaborates closely with Data Engineers, Data Scientists, Architects, Platform Engineers, and business stakeholders.
• Focused on delivering reusable, scalable, secure, and governed platform services across the enterprise Data & AI ecosystem.
• Supports self-service analytics, AI enablement, intelligent data products, and enterprise platform modernization initiatives