Job Description

Key Responsibilities: Design and develop the migration strategies and processes Collaborate with stakeholders to understand business requirements and technical challenges. Analyze current data and scope for optimization during the migration process. Define the architecture and roadmap for cloud-based data and analytics transformation on Databricks. Design, implement, and optimize scalable, high-performance data architectures using Databricks. Build and manage data pipelines and workflows within Databricks. Ensure that best practices for security, scalability, and performance are followed. Implement Databricks solutions that enable machine learning, business intelligence, and data science workloads. Oversee the technical aspects of the migration process, from planning through to execution. Work closely with engineering and data teams to ensure proper migration of ETL processes, data models, and analytics workloads. Troubleshoot and resolve issues related to migration, data quality, and performance. Create documentation of the architecture, migration processes, and solutions. Provide training and support to teams post-migration to ensure they can leverage Databricks. Experience: 7+ years of experience in data engineering, cloud architecture, or related fields. 3+ years of hands-on experience with Databricks, including the implementation of data engineering solutions, migration projects, and optimizing workloads. Strong experience with cloud platforms (e.g., AWS, Azure, GCP) and their integration with Databricks. Experience in end-to-end data migration projects involving large-scale data infrastructure. Familiarity with ETL tools, data lakes, and data warehousing solutions. Skills: Expertise in Databricks architecture and best practices for data processing. Strong knowledge of Spark, Delta Lake, DLT, Lakehouse architecture, and other latest Databricks components. Proficiency in Databricks Asset Bundles Expertise in design and development of migration frameworks using Databricks Proficiency in Python, Scala, SQL, or similar languages for data engineering tasks. Familiarity with data governance, security, and compliance in cloud environments. Solid understanding of cloud-native data solutions and services.