We are seeking an experienced Data Lead with strong expertise in AWS and Databricks to lead the design, development, and modernization of enterprise data platforms. The ideal candidate will have hands-on experience building scalable data solutions in AWS and leading technical teams through cloud-based data transformation initiatives. Responsibilities Experience with Microsoft Azure is highly desirable, as the organization is currently migrating its data platform from Azure to AWS. Lead the design and implementation of modern data platforms using AWS and Databricks. Architect scalable, secure, and high-performance data pipelines. Drive cloud migration initiatives from Azure to AWS. Collaborate with business stakeholders, architects, and engineering teams to define data strategies. Mentor and guide data engineers while ensuring adherence to best practices. Optimize ETL/ELT processes, data models, and data lake architectures. Ensure data quality, governance, security, and performance across the platform. Support Agile delivery and participate in technical planning and solution design Requirements 8+ years of experience in Data Engineering, Data Architecture, or related roles. Bachelor's degree in Computer Science, Information Technology, Software Engineering, Data Science, or a related technical field. Strong hands-on experience with AWS data services. Extensive experience with Databricks, Apache Spark, and Delta Lake. Proficiency in SQL and Python. Experience designing and implementing enterprise-scale data pipelines. Strong understanding of data warehousing, data lakes, and modern data architectures. Excellent leadership, communication, and stakeholder management skills. Preferred Skills Experience with Microsoft Azure data services (ADF, Synapse, ADLS, etc.). Prior experience leading Azure-to-AWS migration projects. Knowledge of CI/CD, Infrastructure as Code (IaC), and DevOps practices. Experience with orchestration tools such as Apache Airflow or AWS Step Functions. AWS and/or Databricks certifications are a plus.