Data Engineer

Tata Consultancy Services is seeking a Data Engineer to design and maintain data pipelines and ETL workflows. The role involves optimizing data processing workloads in Azure and collaborating with stakeholders to ensure data governance and compliance.

Responsibilities:

• Design, develop, and maintain end-to-end data pipelines and ETL/ELT workflows using PySpark and Python
• Implement, optimize, and monitor large-scale data processing workloads in Azure Databricks, including cluster configuration, autoscaling, and governance
• Build and maintain data integration and orchestration solutions using Azure services to meet performance, availability, and security requirements
• Collaborate with data consumers, thread authors/owners, and stakeholders to gather business requirements, prioritize needs, and translate analytical objectives into technical designs
• Implement secure data access patterns using Azure Active Directory, Managed Identities, and service principals
• Author Infrastructure-as-Code for Azure resources (ARM templates) and deploy consistent, repeatable environments
• Configure and operate Azure components including Storage Account, Synapse, Key Vault, VMSS, Function Apps, Web Apps, Log Analytics Workspace, Azure Container Apps / container instances, and related services
• Collaborate with networking and security teams to design and implement Azure networking for data solutions
• Implement monitoring, alerting, and cost optimization for data workloads (Log Analytics, metrics, and dashboards)
• Use GitLab and Azure DevOps for source control, CI/CD pipelines, and release management
• Follow Agile/Scrum practices and participate in sprint planning, standups, and retrospectives
• Ensure solutions meet data governance, lineage, and compliance requirements
• Operations Support and Oncall Support for Production Issues and Deployments

Requirements:

• Strong programming skills in Python and PySpark
• Advanced proficiency writing SQL for analytics and ETL processes
• Proven experience building and optimizing complex data pipelines in Azure
• Hands-on experience with Azure Databricks: cluster management, job scheduling, workspace governance
• Strong working knowledge of core Azure services: Storage Account, Synapse, Key Vault, VMSS, Function Apps, Web Apps, Log Analytics Workspace, service principals, and managed identities
• Experience with container services (ACA, container instances) and containerized data workloads
• Familiarity with Azure networking concepts and secure network integration for data platforms
• Experience creating Azure infrastructure using ARM templates
• Proficient with GitLab and Azure DevOps for CI/CD and source control workflows
• Strong analytical, problem-solving, and communication skills; proven ability to work cross-functionally
• Experience working in Agile teams and understanding of data governance frameworks