Responsibilities:

• Lead high-impact customer engagements focused on Databricks Data Platform solutions.
• Define and drive technical strategies that align Databricks capabilities with customer objectives.
• Architect scalable, secure, and reliable Databricks on AWS platforms, integrating with other AWS services and open-source technologies.
• Provide technical expertise during the pre-sales process, assisting with RFPs/RFIs and creating solution architectures.
• Oversee end-to-end implementation of data platforms, collaborating with cross-functional teams.
• Conduct POCs and technical demos to demonstrate Databricks capabilities.
• Build relationships with customer stakeholders, acting as a trusted advisor on data platform initiatives.
• Promote best practices in data governance, pipelines, and platform architecture.
• Mentor junior team members and contribute to knowledge-sharing efforts.
• Stay current on Databricks and cloud technology advancements.

Requirements:

• Experience in data solution architecture.
• Proven experience in designing and implementing large-scale data engineering solutions on AWS.

• Deep expertise in the Databricks platform.
• Strong knowledge of AWS services such as S3, EC2, Lambda, EMR, Glue, Redshift, AWS MSK, and EKS.
• Proficient in programming languages like Python, SQL, and Scala.
• Experience with data warehousing, ETL processes, and real-time data streaming.
• Familiarity with open-source technologies and tools commonly used in data engineering.
• Excellent communication and presentation skills, with the ability to articulate complex technical concepts to non-technical stakeholders.

• Strong leadership and project management skills.
• Ability to work collaboratively in a cross-functional team environment.

Will Be a Plus:

• AWS Certified Solutions Architect – Professional or similar certifications.
• Databricks Certification (Databricks Certified Professional Data Engineer or equivalent certification).
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

• Experience with AI/ML integration in data platforms.
• Familiarity with data governance tools and practices.
• Contributions to open-source projects or active participation in the data engineering community.