Senior Data Platform Engineer

Glencore

10 - 15 years

14 - 19 Lacs

chennai

Posted:18 hours ago| Platform:

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Skills Required

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Job Type

Full Time

Job Description

Platform Engineering & Architecture
Design and implement scalable, secure, and cost-effective data platform solutions using Azure Synapse Analytics, Azure Data Lake, and related services.
Translate business and regulatory requirements into cloud-native data architectures.
Contribute to the architectural roadmap, including the adoption and integration of Microsoft Fabric for unified data experiences.
Define and enforce platform standards, patterns, and reusable components to accelerate delivery across the team.
CI/CD, Automation & Containerization
Lead the implementation of CI/CD pipelines for data engineering workflows using Azure DevOps and Git.
Automate infrastructure provisioning and deployment using Infrastructure as Code (e.g., Bicep, Terraform).
Develop and maintain containerized data services using Docker, and orchestrate deployments using Kubernetes (AKS).
Establish automated testing, validation, and monitoring practices to ensure data quality and platform reliability.
Team Enablement & Collaboration
Collaborate closely with the other Senior Engineer to co-lead technical direction and ensure consistency across projects.
Mentor and support data engineers and developers, providing guidance on best practices, code reviews, and technical upskilling.
Work cross-functionally with Data Architects, Analysts, and Product Owners to translate business needs into robust data solutions.
Governance, Security & Operations
Implement data governance and lineage practices using Microsoft Purview and Fabric-native tools.
Ensure compliance with security and privacy standards through RBAC, encryption, and secure data handling.
Monitor platform performance and proactively address operational issues and bottlenecks.
Innovation & Continuous Improvement
Stay current with Microsoft s evolving data ecosystem, including Fabric, and evaluate new tools and services for team adoption.
Drive continuous improvement in engineering workflows, platform scalability, and developer experience.
Maintain understanding of the latest trends and advancements in AI and machine learning, and advise on incorporation of these innovations across the department, alongside governance.

COMPETENCIES

Bachelor s degree in Computer Science, Information Technology, or equivalent experience.
Excellent understanding of core data modelling concepts and techniques
Ability to manage stakeholders and develop effective relationships across different cultures.
Cloud & Platform: Azure Synapse Analytics, Microsoft Fabric (emerging), Azure Data Lake Gen2, Azure SQL, Azure DatabricksReal-Time & IoT: Azure Event Hubs, Azure Stream Analytics, Azure IoT Hub
Data Engineering: Azure Data Factory, Synapse Pipelines, Spark, Delta Lake, T-SQL, Python
Governance and Security: Microsoft Purview, Key Vault, RBAC, Data Masking, Encryption
Monitoring and Observability: Azure Monitor, Log Analytics, Application Insights
Governance and Security: Microsoft Purview, Key Vault, RBAC, Data Masking, Encryption
Monitoring and Observability: Azure Monitor, Log Analytics, Application Insights
DevOps and Automation: Azure DevOps, Git/GitHub, CI/CD, Bicep, Terraform, YAML pipelines
Containerization and Orchestration: Docker, Kubernetes (AKS), Helm

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