Full Stack Data Platform Engineer

Vriba; Bengaluru; Híbrido; INR 3.000.000 - 6.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work model

Descripción de la vacante

Vriba in Bengaluru is seeking a highly experienced Full Stack Data Platform Engineer to design, build, and operate enterprise-scale Data & AI platform capabilities for analytics, AI workloads, and autonomous workflows.

The role requires hands-on expertise in AWS, platform engineering, full-stack development, microservices, DevOps, and modern software practices, with collaboration across data engineers, scientists, and stakeholders.

Formación

• Bachelor's degree in Engineering; Master's preferred in CS or IT.
• Hands-on experience building and operating enterprise-grade production platforms.
• Experience with cloud-native architectures and distributed systems.
• Experience building scalable full-stack applications using React, TypeScript/JavaScript, and Node.js.

Responsabilidades

• Design, develop, and enhance Data & AI Platform capabilities for analytics and AI workloads.
• Enable Data Engineering as a Service, Data Quality as a Service, and governance.
• Develop Semantic Layer and Self-Service Analytics capabilities for business users.
• Build cloud-native applications, APIs, platform services, and automation frameworks.
• Ensure security, reliability, and observability across platforms.

Conocimientos

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

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

CI/CD Pipelines

Infrastructure as Code

Terraform

CloudFormation

CDK

Git

Docker

Kubernetes

Platform Monitoring & Observability

Kafka

Data Services

Snowflake

Databricks

Data Warehousing

Lakehouse Architecture

Data Mesh

Data Fabric

Semantic Layers

Self-Service Analytics

Data Governance

Data Quality

Metadata Management

Data Lineage

Generative AI

Agentic AI

Educación

Bachelor's Degree in Engineering

Master's Degree in Computer Science or IT

Herramientas

Snowflake

Databricks

Kafka

AWS Data Services

Descripción del empleo

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

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.
• Strong 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.