Job Overview

Birlasoft is seeking an experienced Cloud Data Platform Engineer / Site Reliability Engineer for a Noida-based opportunity focused on Azure data platforms, Databricks, Microsoft Fabric, infrastructure automation, governance, FinOps, and platform reliability. The role is suited to professionals with 6 to 12 years of experience in cloud data engineering, SRE, platform engineering, or closely related environments.

The position combines cloud operations with data platform engineering. You will help operate and optimize Azure workloads, manage Databricks and Fabric environments, automate infrastructure and deployments, improve cloud cost efficiency, strengthen security controls, and maintain reliable production platforms across development and production stages.

Key Responsibilities

• Manage and optimize Azure data services including ADLS, ADF, Synapse, Key Vault, and VNets.
• Administer Azure Databricks clusters, jobs, DLT pipelines, Delta Lake storage, and Unity Catalog configurations.
• Operate Microsoft Fabric components such as Lakehouses, Pipelines, Warehouses, Dataflows, and Semantic Models for production workloads.
• Maintain consistent platform governance across DEV, QA, UAT, and PROD environments.
• Create and maintain infrastructure provisioning templates using Terraform and Bicep.
• Build CI/CD pipelines for Azure, Databricks, and Fabric components using Azure DevOps or GitHub-based workflows.
• Automate deployment of notebooks, workflows, access policies, networking components, and Fabric artifacts.
• Apply version control, release management practices, and quality gates to platform changes.
• Develop FinOps dashboards, alerts, budgets, and cloud consumption controls.
• Optimize Databricks and Fabric spending through cluster sizing, autoscaling, idle resource management, and workload tuning.
• Perform capacity planning for compute, storage, Fabric engines, and Databricks workloads.
• Manage RBAC, ACLs, Unity Catalog grants, service principals, Managed Identities, and network security controls.
• Support data governance covering access, lineage, audit logging, compliance, and risk reduction.
• Configure secure connectivity using Private Endpoints, VNET integration, and enterprise identity controls.
• Implement monitoring and alerting with Azure Monitor, Log Analytics, Databricks metrics, and Fabric administration interfaces.
• Create operational dashboards, runbooks, and automated remediation workflows.
• Tune data workloads, Databricks jobs, Fabric pipelines, and storage layers for reliability and performance.
• Participate in incident management, root cause analysis, recovery, and platform stabilization activities.

Required Skills

The ideal candidate should have strong hands-on experience operating cloud data platforms rather than only designing them. Practical knowledge of Azure data services is important, particularly ADLS, ADF, Synapse, Key Vault, and VNets.

Strong Azure Databricks experience is required, including clusters, jobs, Delta Lake, Delta Live Tables, and Unity Catalog. Candidates should understand how data workloads are deployed, monitored, secured, and optimized in production.

Experience with Microsoft Fabric is also expected, covering areas such as Lakehouse, Pipelines, Warehouse, and Dataflows. Knowledge of Unity Catalog governance, including catalogs, schemas, access policies, and lineage, is important for enterprise data environments.

Automation skills should include Python, PowerShell, Bash, SQL, and PySpark. Infrastructure as Code experience with Terraform or Bicep is required, along with practical CI/CD experience using Azure DevOps or GitHub Actions.

FinOps knowledge is important because the role includes cloud cost governance, optimization, consumption monitoring, and capacity planning. SRE experience should include concepts such as SLIs, SLOs, operational readiness, automated recovery, monitoring, and incident response.

Preferred Skills

Relevant certifications in Azure Data Engineering, Azure DevOps Engineering, Databricks Data Engineering, or FinOps can strengthen an application. Experience supporting highly regulated industries such as banking and financial services, healthcare, or retail is also useful.

Knowledge of zero-trust security models is preferred for candidates working with enterprise cloud data platforms. Experience designing secure identities, access controls, network boundaries, and governance processes can further strengthen the profile.

Education

The provided job description does not specify a mandatory educational qualification. Candidates should focus on demonstrating relevant professional experience and hands-on expertise in the required cloud data and platform technologies.

Experience

The stated experience range is 6 to 12 years in cloud data engineering, SRE, or platform engineering roles. Candidates should be able to demonstrate production experience with Azure, Databricks, Fabric, automation, infrastructure provisioning, CI/CD, governance, cost management, and platform reliability.

Required Technologies

• Microsoft Azure
• ADLS
• Azure Data Factory
• Azure Synapse
• Azure Key Vault
• Azure Virtual Networks
• Azure Databricks
• Delta Lake
• Delta Live Tables
• Unity Catalog
• Microsoft Fabric
• Fabric Lakehouse
• Fabric Pipelines
• Fabric Warehouse
• Fabric Dataflows
• Semantic Models
• Terraform
• Bicep
• Azure DevOps
• GitHub Actions
• Python
• PowerShell
• Bash
• SQL
• PySpark
• Azure Monitor
• Log Analytics
• Databricks Metrics
• Fabric Admin APIs
• RBAC
• ACLs
• Service Principals
• Managed Identities
• Private Endpoints
• VNET Integration
• CI/CD
• FinOps
• SRE

Soft Skills

This position requires structured problem-solving, operational ownership, and the ability to work through complex cloud platform issues. Strong analytical thinking is important when investigating incidents, identifying root causes, tuning workloads, and evaluating cost or capacity requirements.

Communication is also important because platform engineers work across development, data, security, infrastructure, and business-facing teams. Candidates should be comfortable documenting operational procedures, explaining technical risks, and coordinating incident or change activities.

Benefits of Working in this Role

This role provides broad exposure to modern cloud data platform engineering across Azure, Databricks, and Microsoft Fabric. Professionals can gain deeper experience in infrastructure automation, data governance, FinOps, observability, SRE, security, and production platform operations.

The combination of cloud data engineering and SRE responsibilities can also help experienced professionals develop skills relevant to senior platform engineering, cloud architecture, data platform leadership, and cloud reliability roles.

Work Mode

The provided job description does not explicitly state whether the role is onsite, hybrid, or remote.

Location

The job is listed in Noida, Uttar Pradesh, India.

Who Should Apply

This opportunity is intended for experienced professionals with 6 to 12 years of relevant cloud data engineering, SRE, or platform engineering experience. It is not a fresher role.

Candidates should be comfortable managing production Azure data environments and should have practical experience with Azure Databricks, Microsoft Fabric, Unity Catalog, Infrastructure as Code, CI/CD, cloud cost optimization, security, monitoring, and reliability engineering.

Career Growth

Experience in this position can support progression into roles such as Senior Cloud Data Engineer, Data Platform Engineer, Cloud SRE, Azure Data Platform Architect, Cloud Platform Lead, Databricks Platform Engineer, or Data Engineering Manager. Exposure to FinOps, security, governance, and SRE practices can broaden opportunities in enterprise cloud engineering.

Application Advice

Tailor your resume around the technologies and responsibilities that match the role. Clearly describe your hands-on experience with Azure, Databricks, Microsoft Fabric, Unity Catalog, Terraform or Bicep, and CI/CD.

Include practical examples of platform automation, cost optimization, monitoring, incident response, security governance, and performance tuning. If you have certifications in Azure Data Engineering, Azure DevOps, Databricks Data Engineering, or FinOps, list them clearly.

Candidates with regulated-industry experience should mention the type of environment supported and the governance or compliance responsibilities handled. Keep all technology claims accurate and focus on measurable production outcomes where possible.