Data Architect

Were Hiring: Azure Databricks Data Architect OwlSure, A Business Unit of ValueMomentum

Seniority Level: Architecute

Industry: IT Services and IT Consulting

Job Function: Data Architecture | Cloud Engineering | Information Technology

About OwlSure

OwlSure enables Financial Services, Healthcare, and Life Insurance organizations to achieve value for their budgets, accelerate speed-to-market, and scale operations. Through thoughtfully designed solutions and highly automated managed services, we deliver reliable outcomes backed by deep technical expertise and a continuously optimized delivery platform.

Job Title: Azure Databricks Data Architect

Role Summary

The Azure Databricks Data Architect is responsible for designing and implementing modern, cloud-native data platforms that support enterprise-scale analytics, BI, and data-driven decision-making.

This role leads end-to-end architecture for data modernization initiativesfrom ingestion to consumptionleveraging Azure services and Databricks to build scalable, secure, and cost-effective solutions. The architect will also drive DataOps and MLOps frameworks, CI/CD automation, and internal capability development.

Key Responsibilities

Data Architecture & Modernization

• Design modern, scalable data architectures for cloud-native platforms.
• Lead architecture and implementation of end-to-end data solutions on Microsoft Azure.
• Define ingestion-to-consumption frameworks supporting:
• Modern Data Warehouses
• BI & Reporting
• Advanced Analytics & Insights
• Conduct data strategy sessions focused on scalability, flexibility, and performance optimization.
• Design data models aligned with enterprise data governance standards.

Platform Engineering & Implementation

• Build cost-efficient infrastructure using:
• Azure Databricks
• Azure Data Factory
• Develop data pipelines using Databricks, PySpark, and modern ELT/ETL patterns.
• Implement CI/CD pipelines for Databricks using Azure DevOps.
• Lead migrations from on-premises platforms (Spark, Hadoop) to Databricks-based architectures.

Data Engineering & Processing

• Implement advanced data processing frameworks (Spark, PySpark).
• Design and optimize cloud-native databases and columnar storage architectures.
• Work with processing substrates such as ETL tools, Kafka, and ELT techniques.
• Enable Data Mesh and Data Product architecture where applicable.

DataOps & MLOps

• Build and operationalize DataOps and MLOps frameworks.
• Establish automation standards for testing, deployment, and monitoring.
• Ensure governance, security, and compliance within data platforms.

Stakeholder & Team Collaboration

• Collaborate with Data Engineering, Data Management, BI, and Analytics teams.
• Partner with customers on enterprise data modernization initiatives.
• Create training plans and learning materials to upskill internal associates.
• Develop reusable, domain-specific accelerators and industry-focused data solutions.

Required Skills & Experience

Experience

• 10+ years of overall IT experience.
• Minimum 4+ years implementing cloud-native end-to-end data solutions.
• Proven experience delivering Modern Data Warehouse and analytics platforms.
• Experience working in complex enterprise IT environments.

Technical Skills

• Strong expertise in Azure-based modern data architecture.
• Hands-on experience with:
• Azure Databricks
• PySpark
• Azure Data Factory
• Experience migrating on-prem platforms (Spark, Hadoop) to cloud-native architectures.
• Strong understanding of data warehouse concepts and columnar database design.
• CI/CD implementation using Azure DevOps.
• Experience with ETL tools, Kafka, and ELT frameworks.
• Proficiency in data governance and cloud-native architecture patterns.

Methodology & Collaboration

• Understanding of Agile/Scrum methodologies.
• Ability to collaborate across cross-functional teams (Data Engineering, BI, Analytics).
• Strong stakeholder communication and architecture documentation skills.

Preferred Qualifications

• Experience designing and implementing Data Mesh or Data Product architectures.
• Exposure to MLOps frameworks and advanced analytics platforms.
• Domain experience in enterprise data modernization programs.

Why Join OwlSure?

• Lead enterprise-scale cloud data transformation programs.
• Work with global clients across Insurance, Healthcare, and Financial Services.
• Shape next-generation data platforms leveraging Azure and Databricks.
• Contribute to a growing data and analytics practice with strong innovation focus.