Data Architect

Role Summary:

We are seeking an experienced Databricks Architect to lead the design and implementation of enterprise-scale data and reporting solutions. The role will focus on architecting modern lakehouse environments, designing scalable data models, building curated reporting datasets, and enabling high-quality analytics through Databricks-based platforms. The ideal candidate will combine deep technical expertise with strong stakeholder collaboration skills to support enterprise reporting and analytical initiatives.

Scope of Work & Key Responsibilities:

• Assess existing data sources, transformations, reporting requirements, and data flows across the enterprise.
• Define and implement scalable Databricks lakehouse architectures supporting reporting and analytics workloads.
• Design enterprise data models, curated datasets, semantic layers, and source-to-target mappings.
• Provide architectural guidance for Databricks notebooks, workflows, jobs, Delta tables, and orchestration processes.
• Design and optimize data ingestion, transformation, and processing pipelines.
• Establish data quality, reconciliation, metadata, lineage, governance, and auditability frameworks.
• Implement security controls, role-based access models, and data protection policies.
• Optimize Databricks workloads, SQL queries, storage structures, and resource utilization for performance and scalability.
• Support integration of Databricks data products with reporting and visualization platforms.
• Troubleshoot and resolve technical and data-related issues during development, testing, and deployment.
• Support SIT, UAT, production readiness, and post-deployment activities.
• Create architecture documents, technical specifications, and knowledge transfer materials.
• Collaborate with product owners, business analysts, data engineers, and reporting teams within Agile delivery environments.

Required Skills & Experience:

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or related discipline.
• 8+ years of experience in data architecture, data engineering, analytics platforms, or related domains.
• Strong hands-on experience with Databricks and modern lakehouse architectures.
• Proven expertise designing scalable enterprise data solutions and reporting data models.
• Experience with:
  • Databricks Notebooks
  • Jobs & Workflows
  • Delta Lake
  • SQL
  • Data Transformation Frameworks
• Strong SQL expertise and experience handling large-scale data processing workloads.
• Experience building ingestion and transformation pipelines from multiple enterprise data sources.
• Strong understanding of:
  • Data Quality
  • Reconciliation
  • Metadata Management
  • Data Lineage
  • Data Governance
• Experience implementing role-based access controls, security frameworks, and enterprise data policies.
• Proven track record optimizing Databricks performance, storage design, and workloads.
• Experience building curated data products, semantic layers, and enterprise reporting datasets.
• Ability to translate business requirements into scalable technical architectures and implementation designs.
• Strong documentation, communication, and stakeholder management skills.
• Experience working in Agile/Scrum teams and collaborating across business and technical functions.

Preferred Skills:

• Experience with Power BI or other enterprise reporting and visualization platforms.
• Exposure to Azure Data Factory, Azure Synapse, Azure Data Lake Storage, or similar cloud data services.
• Experience with Unity Catalog, data governance platforms, or enterprise metadata solutions.
• Knowledge of DataOps, CI/CD, and automated deployment practices for data platforms.
• Experience supporting enterprise reporting, executive dashboards, and analytics modernization initiatives.