DataBricks Data Architect Exp 13 Yrs To 18 Yrs

Job Description: DataBricks – Data Architect (Exp: 13 Yrs to 18 Yrs)

We are seeking a talented and motivated DataBricks expert to join our team as a Data Architect.

Required Skills & Qualifications

• 13+ years of IT experience, with 3+ years focused on Databricks and cloud data ecosystems.
• Advanced PySpark and SQL skills, with proficiency in Python, Scala, or Java.
• Deep knowledge of Delta Lake, MLflow, Unity Catalog, and Serverless Compute.
• Hands-on expertise in Microsoft Azure (Azure Databricks), AWS, or Google Cloud Platform.
• Strong background in dimensional modeling, star/snowflake schemas, and data warehousing principles.
• Experience with streaming data (Structured Streaming, Kafka, Event Hubs, Pub/Sub).
• Experience with Infrastructure-as-Code (Terraform) and CI/CD for data platforms.
• Experience in pre-sales, solution proposals, and client-facing architecture discussions.
• Experience in agile development processes using Jira and Confluence.
• Own the data platform architecture and guide its delivery on Databricks.
• Understanding of the SDLC and Agile methodologies.
• Communication with the customer and producing the daily status report.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Databricks Certified Data Engineer Professional certification.
• Cloud architect certification (Azure Solutions Architect Expert, AWS Solutions Architect - Professional, or Google Professional Cloud Architect).
• Should have good oral and written communication.
• Should be able to present solutions to business and technical stakeholders.
• Should be proactive and adaptive.
  
  

• Create scalable data platform blueprints using the Lakehouse and Medallion architecture (Bronze, Silver, Gold layers).
• Manage performance tuning, cluster configurations, and cost optimization across cloud environments (Azure, AWS, or GCP).
• Implement security, access control, and data lineage using Unity Catalog.
• Oversee ELT/ETL processes, automated workflows, and job scheduling via Databricks Jobs and Delta Live Tables.
• Partner with data engineers, data scientists, and stakeholders to align technical solutions with business goals.