Data Platform Engineer (Azure) (CPT)

📍   |   🏷️   |   🕒 January 19, 2026
DevOpsGitHubMicrosoft AzurePythonSQL Server
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Employment Type Full Time
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Experience 7 to 10 years
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Salary Cost To Company
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Published 19 Jan 2026
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Reference ID 2261416850

ENVIRONMENT:

A renowned Independent Asset Management Firm seeks a Data Platform Engineer in a hands-on Engineering role with a blend of architectural design, DevOps and governance responsibilities across Azure, Databricks, and on-premises environments. You will play a pivotal role in building, maintaining, and evolving the firm’s Enterprise Data Platform from existing hybrid on-prem SQL and Azure Cloud technologies, into a fully Azure Cloud and Databricks architecture. You will ensure a secure, scalable, and performant data platform infrastructure — enabling Analytics, Data Science, and Enterprise Data Integration across the business. The ideal candidate will require a BSc Computer Science or equivalent, Microsoft AZ and/or DP Certifications, Databricks Data Platform, Data Engineer, Platform Architect Certifications and 7-10 years technology experience with proficiency in Azure Cloud Services, Bicep, Terraform, SQL Server, Python & FinOps awareness and cloud cost optimization experience.

 

DUTIES:

Platform Engineering & Management –

  • Build, configure, and manage Azure infrastructure components supporting the Core Data Platform.
  • Develop and maintain Infrastructure-as-Code using Bicep and Terraform.
  • Manage and maintain the Azure Databricks environments, including workspace creation, access management, and environment configuration.
  • Oversee Azure DevOps and GitHub pipelines for CI/CD of data infrastructure and integration components.
  • Implement FinOps practices to optimize cloud cost management and forecasting.

 

Database & Integration Management –

  • Support on-premises SQL Server environments (3rd Line), including performance troubleshooting, tuning, and high-availability configurations.
  • Collaborate with Data Integration teams to ensure smooth data movement between on-premises and cloud environments.
  • Oversee and maintain secure, high-performance data pipelines and connectivity between systems.

 

Security, Governance & Compliance –

  • Design and enforce role-based access controls (RBAC) across the Databricks platform and Core Data subscriptions.
  • Ensure compliance with internal security policies, regulatory standards, and data governance frameworks.
  • Implement and maintain platform monitoring, logging, and alerting for proactive issue resolution.

 

Architecture & Standards –

  • Contribute to architectural design and technical standards for Azure and Databricks solutions.
  • Evaluate and recommend improvements to infrastructure patterns and automation processes.
  • Ensure platform architecture aligns with best practices, scalability, and resilience requirements.

 

Collaboration & Continuous Improvement –

  • Partner with Data Engineering, Architecture, and Security teams to deliver end-to-end solutions.
  • Mentor junior engineers and promote knowledge sharing within the Core Data team
  • Identify automation opportunities to improve efficiency and platform reliability.

 

REQUIREMENTS:

Qualifications –

  • BSc Computer Science or equivalent.
  • Microsoft AZ and/or DP Certifications.
  • Databricks Data Platform, Data Engineer, Platform Architect Certifications.

 

Experience/Skills –

  • 7-10 Years technology experience, with at least 3 years in the cloud platform/data platform roles.
  • Azure Cloud Services (compute, networking, storage, security, cost management).
  • Infrastructure as Code: Bicep and Terraform.
  • Azure Databricks management (workspace setup, security, clusters, policies).
  • Azure DevOps and/or GitHub Actions pipeline management.
  • Python scripting for automation and tooling.
  • SQL Server administration and performance tuning (3rd-line level).
  • FinOps awareness and cloud cost optimization experience.

 

Advantageous –

  • Experience with Azure Monitor, Log Analytics, and Application Insights.
  • Knowledge of data governance tools.
  • Familiarity with CI/CD principles for data pipelines.
  • Understanding of data integration frameworks and patterns (ETL/ELT).
  • Exposure to enterprise identity management (Entra ID).

 

ATTRIBUTES:

  • The ability to ‘approach and own’ and continuously looks for opportunities to develop.
  • High conviction and be comfortable sharing opinions.
  • The ability to build and maintain meaningful relationships.
  • A client-focused and collaborative approach.
  • A curiosity about technology and its potential to drive innovation.

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