Job Title

Data Architect – Databricks (Azure/AWS) Role Overview: We are seeking an experiencedData Architectspecializing inDatabricksto lead the architecture, design, and migration of enterprise data workloads from on-premises systems (e.g., Oracle, Exadata, Hadoop) toDatabricksonAzureorAWS . The role involves designing scalable, secure, and high-performing data platforms based on themedallion architecture(bronze, silver, gold layers), supporting large-scale ingestion, transformation, and publishing of data. Key Responsibilities: Define and design cloud-native data architecture on Databricks using Delta Lake, Unity Catalog, and related services. Develop migration strategies for moving on-premises data workloads (Oracle, Hadoop, Exadata, etc.) to Databricks on Azure/AWS. Architect and oversee data pipelines supporting ingestion, curation, transformation, and analytics in a multi-layered (bronze/silver/gold) model. Lead data modeling, schema design, performance optimization, and data governance best practices. Collaborate with data engineering, platform, and security teams to build production-ready solutions. Create standards for ingestion frameworks, job orchestration (e.g., workflows, Airflow), and data quality validation. Support cost optimization, scalability design, and operational monitoring frameworks. Guide and mentor engineering teams during the build and migration phases. Required Skills and Experience: 10+ years of experience in data architecture or engineering roles, with at least 3+ years specializing in cloud-based big data solutions. Hands-on expertise withDatabricksonAzureorAWS . Deep understanding ofDelta Lake ,medallion architecture(bronze/silver/gold zones), and data governance tools (e.g., Unity Catalog, Purview). Strong experience migrating large datasets and batch/streaming pipelines from on-prem to Databricks. Expertise with Spark (PySpark/Scala) at scale and optimizing Spark jobs. Familiarity with ingestion from RDBMS (Oracle, SQL Server) and legacy Hadoop ecosystems. Proficiency in orchestration tools (Databricks Workflows, Airflow, Azure Data Factory, AWS Glue Workflows). Strong understanding of cloud-native services for storage, compute, security, and networking. Preferred Qualifications: Databricks Certified Data Engineer or Architect. Azure/AWS cloud certifications. Experience with real-time/streaming ingestion (Kafka, Event Hubs, Kinesis). Familiarity with data quality frameworks (e.g., Deequ, Great Expectations).