Databricks Architect

Your Role and Impact

Databricks Architect

Databricks features

Delta Lake, Unity Catalog, Databricks SQL

Azure Data Factory (ADF)

• 8+ years of extensive knowledge of Databricks features: Delta Lake, Unity Catalog, Databricks SQL, MLflow.
• Strong experience with Azure Data Factory for orchestration and integration.
• Hands-on expertise in performance optimization and writing complex SQL queries.
• Solid understanding of cloud architecture, security, and governance best practices.
• Excellent problem-solving and troubleshooting skills for large-scale data pipelines.
  

Preferred Experience:

Certifications

• Databricks Certified Data Engineer or Architect.
• Microsoft Azure certifications (e.g., Azure Data Engineer Associate).
  

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent communication and stakeholder management skills.
• Ability to lead and mentor technical teams.
  

Your Contribution

Architecture Assessment & Design

• Design and implement scalable, secure data architectures leveraging Databricks and Azure Data Factory.
• Develop frameworks for data ingestion, transformation, and analytics using Delta Lake, Unity Catalog, and Databricks SQL.
• Optimize Spark jobs, SQL queries, and pipelines for performance and cost efficiency.
• Collaborate with data engineers, analysts, and business stakeholders to deliver robust solutions.
• Implement governance, security, and compliance standards, including RBAC and data lineage.
• Ensure high availability and reliability through proactive monitoring and troubleshooting.
  

Strategic & Business Alignment

• Translate strategic business objectives into enterprise-wide data architecture solutions.
• Align data architecture with organizational priorities, ensuring data capabilities support analytics, reporting, and advanced use cases (AI/ML).
• Define and enforce architecture principles, standards, and governance frameworks.
  

Technical Leadership

• Guide cross-functional teams in adopting architectural patterns and best practices.
• Lead the selection of appropriate data platforms, tools, and frameworks.
• Champion the adoption of DataOps practices for faster, automated, and high-quality data delivery.
• Promote ETL automation using AI/ML-driven solutions to optimize data ingestion, transformation, and error detection.
  

Presales & Client Engagement

• Support presales and solution design activities, working alongside Sales, Product, and Customer Success teams.
• Participate in client discovery calls, architecture reviews, and solution presentations.
• Develop high-level architecture overviews and proof-of-concepts for client proposals.