Lead Engineer, EDT Data & Analytics Cloud Engineering

Stryker Group; Gurugram District; On-site; INR 3,500,000 - 5,200,000; Full time

Job summary

Stryker Group is seeking a Lead Engineer for EDT Data & Analytics Cloud Engineering to own Azure-based data platform operations and DevOps automation. You will design pipelines, automate IaC, and reinforce security across Databricks, Synapse, and related services.

You will collaborate with data platform and product teams to deploy ingestion pipelines, Databricks jobs, and governance-enabled workflows, ensuring reliability and compliance.

Qualifications

• Bachelor's or Master's degree in computer science, engineering, information systems, or a related technical discipline.
• 5-7 years of experience designing, engineering, and supporting cloud-based data and analytics platforms.
• Strong hands-on expertise with Azure data services (Databricks, Synapse, ADLS Gen2, Azure SQL, Data Factory, Key Vault, Unity Catalog).
• Proven experience implementing platform security controls, governance frameworks, and Azure data platform best practices.
• Proficiency in IaC using Terraform and Azure DevOps CI/CD pipelines, with experience automating deployments across environments.
• Demonstrated ability to monitor, optimize, and troubleshoot cloud data platforms with incident management and root-cause analysis.

Responsibilities

• Design, build, test, and operate Azure DevOps CI/CD pipelines packaging code, running quality checks, and deploying infrastructure and data workloads.
• Own pipeline execution and release readiness, monitoring runs and improving rollback and promotion controls.
• Write and maintain Terraform modules for Azure/Databricks provisioning; test changes through plan and deployment cycles.
• Provision and configure workspaces, compute, storage, networking, and access via automated IaC processes.
• Configure and troubleshoot RBAC, service principals, secrets, and Unity Catalog grants across data services.
• Build monitoring, alerts, dashboards, and runbooks; participate in incident response and root-cause analysis.
• Collaborate with Data Platform and Data Product teams to deploy ingestion pipelines, Databricks jobs, and platform services.
• Translate stakeholders into implementable changes; document solutions and handoffs.

Skills

DevOps automation

Cloud data platform design

Monitoring & incident mgmt

Security by default

Cross-functional collaboration

Education

Bachelor's/Master's in CS/Engineering/IS

5-7 years cloud data platform exp

Tools

Azure Databricks

Azure Synapse

ADLS Gen2

Azure SQL

Azure Data Factory

Unity Catalog

Terraform

Azure DevOps

Job description

Lead Engineer, EDT Data & Analytics Cloud Engineering

The Lead Cloud Platform Engineer supports the operational excellence, security, and reliability of the enterprise data & analytics platform on Azure and Databricks. The role combines platform operations, DevOps automation, and Infrastructure as Code across the core stack - Azure Databricks, Synapse, ADLS Gen2, Azure SQL, Azure Data Factory, Key Vault, and Unity Catalog - with a reliability-engineering mindset: automate repeatable work, apply security best practices by default, and help keep the platform highly available for global data engineering and analytics teams.

What you will do:

DevOps Pipeline Management & CI/CD

• Design, build, test, and operate Azure DevOps CI/CD pipelines that package code, run automated quality checks, deploy infrastructure and data workloads, and promote releases across development, testing, and production environments.
• Own day-to-day pipeline execution and release readiness by monitoring runs, diagnosing failed builds and deployments, correcting pipeline definitions, and improving rollback, approval, and promotion controls.

Infrastructure as Code & Environment Provisioning

• Write, review, and maintain Terraform modules for repeatable provisioning of Azure and Databricks platform components; test changes through plan and deployment cycles and keep modules versioned and reusable.
• Provision and configure workspaces, compute, storage, networking, private connectivity, identities, and access through automated IaC processes; detect configuration drift and implement corrective changes.

Platform Security & Access Management

• Configure and troubleshoot RBAC, service principals, managed identities, secrets, storage permissions, cluster policies, and Unity Catalog grants across Azure Data Factory, Databricks, Synapse, Azure SQL, ADLS Gen2, and Key Vault.
• Apply and verify least-privilege access, identity integration, and secrets-management controls through hands‑on configuration reviews, access testing, and remediation of security findings.

Platform Operations & Reliability Engineering

• Build and tune monitoring, alerts, dashboards, and operational runbooks; participate directly in incident response, perform root-cause analysis, and implement preventive automation and reliability fixes.
• Monitor integration runtimes, clusters, jobs, pipelines, and platform services; inspect logs and metrics, reproduce failures, resolve runtime and performance issues, and validate service recovery against SLAs.

Data Engineering Operations

• Work directly with Data Platform and Data Product teams to deploy and operationalize ingestion pipelines, orchestration, Databricks jobs, and supporting platform services; provide hands‑on support through production rollout.

Collaboration

• Translate stakeholders into implementable technical changes, contribute code and configuration, lead technical working sessions, and document the resulting solution and operational handoff.

What you need:

• Bachelor’s or master’s degree in computer science, Engineering, Information Systems, Business, or a related technical discipline.
• 5-7 years of experience designing, engineering, and supporting cloud-based data and analytics platforms, data warehouses, and modern data ecosystems.
• Strong hands‑on expertise with Azure data services, including Azure Databricks, Synapse Analytics, ADLS Gen2, Azure SQL, Azure Data Factory, Key Vault, and Unity Catalog.
• Proven experience implementing platform security controls, governance frameworks, and Azure data platform best practices to ensure secure, scalable, and compliant solutions.
• Proficiency in Infrastructure as Code (IaC) using Terraform and Azure DevOps CI/CD pipelines, with experience automating deployments across multiple environments.
• Demonstrated ability to monitor, optimize, and troubleshoot cloud data platforms, including performance tuning, alerting, incident management, and root‑cause analysis.
• Excellent analytical, problem‑solving, and communication skills, with the ability to collaborate effectively across engineering, operations, security, and business stakeholders.
• Proactive mindset with a track record of driving automation, process optimization, operational improvements, and scalable platform enhancements that increase efficiency and reliability.
• Cloud Engineering certifications on Azure/Databricks platform is a plus.