We are seeking a hands-on Data & AI Automation Engineer II to build and operate shared data, automation, and AI capabilities for the Msec Unified data platform. You will develop reliable data pipelines, automate operational workflows, integrate copilots and intelligent agents, and create reusable services that make governed Platform data easier to discover and use . Data and Platform Engineering Design and operate batch and near-real-time pipelines using Azure data services, Fabric ,Kusto, SQL, Python, and APIs. Build governed ingestion, transformation, allocation, and serving layers for cost, spend, utilization, efficiency, customer, and operational data. build intelligent systems for data quality, schema validation, lineage, reconciliation, metadata, freshness monitoring, and performance optimization. Create reusable data products, semantic models, APIs, and self-service interfaces with clear definitions and ownership. Redesign existing workflows into AI native /Integrated workflow Automation and Software Development Develop Python services, APIs, command-line tools, scheduled jobs, and event-driven workflows. Automate pipeline monitoring, data validation, failure investigation, reporting, notifications, and approved recovery actions. Replace spreadsheet-dependent and repetitive operational processes with governed automation. Apply and automate source control, testing, code reviews, CI/CD, secure configuration, documentation, and production-readiness practices. AI, Copilot, and Agent Integration Build copilots and agents grounded in governed Platform data and connected to Kusto, APIs, knowledge sources, and operational systems.



Enabling near real time support to platform users and responses on bugs . Develop retrieval, prompt orchestration, agent tools, MCP integrations, reusable AI services, and evaluation frameworks. Enable AI-assisted failure analysis & action for Data orchestrations layer Ensure AI solutions are secure, observable, evaluated, cost-conscious, and compliant with data and responsible-AI requirements. Reliability and Operational Excellence Implement telemetry, health dashboards, alerts, data-freshness controls, anomaly detection, and automated status reporting. Investigate incidents, missing or stale data, schema changes, performance issues, and pipeline failures; drive root-cause remediation. Improve platform availability, scalability, supportability, and cost efficiency while reducing manual operational effort. Partnership and Ownership Translate business and operational needs into scalable technical designs and independently deliver medium-complexity solutions. Communicate architecture decisions, trade-offs, risks, and recommendations to technical and non-technical stakeholders. Coordinate with platform and source-system owners, validate requirements, and promote shared components over one-off implementations. High level of accountability and responsiveness for the assigned work item Bachelor's degree in Computer Science, Engineering, Data Science,



Information Systems, or equivalent practical experience. Approximately 3-6 years of experience in data, software, AI, or automation engineering. Solid Python and SQL skills with experience building production data pipelines or cloud-based processing systems. Experience integrating systems through APIs or SDKs and applying testing, source control, CI/CD, and deployment practices. Understanding of data modeling, quality, lineage, monitoring, security, and operational support. Experience building GenAI applications, copilots, agents, RAG solutions, or Model Context Protocol integrations. Experience with FastAPI, Azure DevOps, Teams integrations, telemetry, incident management, and workflow automation. Knowledge of managed identity, RBAC, secret management, data governance, privacy, compliance, and responsible AI. Independently owns features, automation workflows, services, or data domains from design through production. Produces secure, maintainable, tested, observable, and scalable solutions with minimal supervision. Identifies risks and dependencies early, delivers predictably, and resolves root causes rather than symptoms. Builds reusable capabilities, measures automation value, and checks for existing solutions before creating new ones. Connects data, AI, governance, infrastructure, and operations to deliver measurable business value. Collaborates effectively and communicates clearly with engineering, product, and business stakeholders. This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. *

📌 Data Engineer II (Bengaluru)
🏢 Microsoft
📍 Bengaluru