H i,

I hope you are d oing great.

Please s hare your u pdated resume if you want to apply for the position below.

Job Title Solution Architect Data & Machine Learning Platform (MLP)

Location Bangalore (Onsite)

Interview Mode- Video

Duration: 6+ Months Contract to Hire

Position Overview

We are looking for a highly skilled Solution Architect to lead the design and implementation of a Data and Machine Learning Platform spanning edge, cloud, and on-prem components. The ideal candidate will have deep experience in Azure cloud services, data engineering, edge computing, and ML lifecycle management.

Technical Expertise

Azure Cloud Stack & DevOps

Azure Databricks (including ML workspace for Feature Store and Model Store)

Azure Data Factory (ADF) for orchestration and compute

Azure Data Lake Storage (ADLS) implementing medallion architecture (raw, bronze, silver, gold)

Azure Event Hub: Experience in defining topics, managing consumer groups, and integrating ETL events

Azure Streaming Analytics: Real-time data processing for telemetry and operational data

Azure Key Vault

Azure App Service

Azure Container Registry (ACR)

Azure IoT Hub for connecting edge devices

Azure DevOps & GitHub Actions (for CI/CD pipelines)

GitHub self-hosted runners for ML workflow automation

Edge and On-Prem Integration

Strong experience in OT-IT integration and data extraction from industrial systems

Edge VM deployment using:

- Docker and Portainer for container orchestration

- RabbitMQ for messaging (read/write services from edge)

- OPC UA for interfacing with PLCs (e.g., FX Filter, NH3 Compressor)

- IDMZ deployment practices and edge-to-cloud data service integration

Machine Learning Platform (MLP) and MLOps

End-to-end ML lifecycle implementation: Feature Engineering, Model Training & Validation, Model Export, Versioning, and Deployment

Hands-on with ADB ML workspace, Feature Store, Model Store

Monitoring deployed models at 1-minute intervals

Understanding of training vs inference, cloud vs edge deployment

Cadence for ML models (Weekly Refresh, Monthly Retrain, Quarterly Revamp)

Use of GitHub monorepo structure for managing model code

Data Architecture & Integration

Implementation of medallion architecture in the data platform

Integration with Unity Catalog (UC) for governance, data sharing, and cataloging

Experience with CDC tools (e.g., Aecorsoft) for real-time SAP data ingestion

Consumption layer design for BI, ML, and operational workloads

Familiarity with streaming and API-based ingestion from external environments

Template-driven ingestion and mapping using configurations

Governance and Data Modeling

Define and enforce data governance standards using Unity Catalog and enterprise frameworks. Design scalable data models to support operational analytics and ML features. Implement policies for access control, quality, and metadata tagging across DLZ/zones.

Key Responsibilities

Architect Integrated Solutions: Lead architectural design across edge, cloud, and ML across zones

Build and Govern Data Platform: Oversee ingestion, transformation, and cataloging across Raw Gold layers, aligned to UC.

Enable Scalable ML Platform: Support ML teams with infrastructure for feature storage, model ops, and deployment pipelines.

Edge Integration and Automation: Design robust and secure OT-IT interfaces with RabbitMQ, OPC UA, and container orchestration tools.

Monitor and Optimize Pipelines: Set up real-time monitoring for ML and ETL pipelines; optimize for performance and cost.

Governance and Security Compliance: Ensure enterprise compliance, tagging, and secure access across all zones and services.

Lead CI/CD Automation: Use GitHub Actions and Azure DevOps to streamline deployment of ML workflows and platform components.

ion Architect - Data & Machine Learning Platform (MLP)

Job Description

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