Data Architect

About the Company

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About us:

Cloud RaptorCloud Raptor is a modern technology and digital transformation partner helping organisations design, build, and scale intelligent, future-ready solutions. We exist to close the gap between business ambition and technology execution—delivering outcomes that are measurable, secure, and built to last.

Our teams bring together experienced consultants, product specialists, and certified engineers with deep expertise across cloud platforms, enterprise software engineering, DevOps, AI/ML, cybersecurity, and large-scale digital transformation. We work closely with our clients to modernise legacy environments, optimise operations, and launch digital products that create real competitive advantage.

We support organisations across BFSI, Retail, Utilities, Education, and the Public Sector, delivering tailored solutions that align with each client's strategic goals, risk profile, and growth roadmap. Our approach blends strong domain knowledge with pragmatic delivery—ensuring technology decisions translate into real business value.

Headquartered in Australia, with delivery hubs across India, the Philippines, the UK, the US, and the UAE, Cloud Raptor combines global scale with strong local expertise. Whether modernising core platforms, scaling cloud infrastructure, or building AI-driven products, we help organisations move faster with confidence.

At our core, Cloud Raptor is built on long-term partnerships, continuous learning, and outcome-driven delivery. We don't just implement technology—we help shape what's next.

Let's calibrate your future with technology.

About the Role

Data Architect - Azure Databricks Expert

Role Overview

We are seeking a highly skilled and experienced Data Architect with deep expertise in Azure Databricks to lead the design, implementation, and optimization of scalable data solutions. The ideal candidate will have a strong background in cloud-based data architecture, big data processing, and advanced analytics, with a focus on leveraging Azure Databricks for enterprise-grade solutions.

Responsibilities

• Architect and design end-to-end data solutions using Azure Databricks, Delta Lake, and other Azure data services.
• Lead the deployment and operationalization of Databricks environments, ensuring scalability, performance, and security.
• Collaborate with data engineers, analysts, and business stakeholders to define data models, pipelines, and governance frameworks.
• Develop and enforce best practices for data ingestion, transformation, and storage using Spark and Databricks notebooks.
• Optimize data workflows for cost-efficiency and performance across Azure services.
• Implement CI/CD pipelines for Databricks notebooks and jobs using tools like Azure DevOps or GitHub Actions.
• Ensure compliance with data security, privacy, and governance standards.
• Provide technical leadership and mentorship to junior data engineers and architects.
• Stay current with emerging technologies and trends in cloud data architecture and analytics.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Systems, or related field.
• 7+ years of experience in data architecture, with at least 3 years focused on Azure Databricks.
• Expert-level proficiency in Apache Spark, Delta Lake, and Databricks SQL.
• Strong experience with Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory, and Azure DevOps.
• Proven track record in designing and deploying large-scale data platforms in Azure.
• Solid understanding of data modeling, ETL/ELT processes, and data governance.
• Experience with Python, Scala, and SQL in a big data context.
• Familiarity with MLflow, Unity Catalog, and Databricks Workflows is a plus.
• Excellent communication and stakeholder management skills.

Required Skills

• Azure Databricks
• Apache Spark
• Delta Lake
• Databricks SQL
• Azure Data Lake Storage
• Azure Synapse Analytics
• Azure Data Factory
• Azure DevOps
• Data modeling
• ETL/ELT processes
• Data governance
• Python
• Scala
• SQL
• Communication and stakeholder management

Preferred Skills

Preferred Qualifications

• Experience with real-time data streaming using Azure Event Hubs or Kafka.
• Knowledge of data mesh architecture and domain-oriented data ownership.
• Hands-on experience with Databricks Lakehouse Platform.
• Understanding of data privacy regulations (e.g., GDPR, HIPAA) and how they impact cloud data architecture.
• Experience integrating Databricks with Power BI, Tableau, or other BI tools.
• Exposure to machine learning workflows and MLOps practices in Databricks.
• Strong problem-solving skills and ability to work in fast-paced environments.
• Certification in Databricks Lakehouse Fundamentals or Advanced Data Engineering.