Senior Data Solutions Architect With Aws

Responsibilities:

• Strategic Technical Leadership

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  Lead complex, high-impact customer engagements focused on AWS Data Platform solutions.
• Define and drive technical strategies that align AWS capabilities with customer business objectives, incorporating Databricks (as a plus) solutions where appropriate.

• Solution Architecture and Design

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  Architect and design scalable data platforms using AWS, ensuring optimal performance, reliability, security, and cost efficiency.
• Evaluate and select appropriate technologies and tools to meet customer needs, integrating AWS services with other solutions such as Databricks, and Snowflake as necessary.
• Establish, fulfill, and maintain comprehensive architectural documentation to ensure alignment with technical standards and best practices across the organization.

• Pre-Sales Activities

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  Collaborate with the sales team during the pre-sales process by providing technical expertise to position AWS-based data solutions effectively.
• Participate in customer meetings to assess technical needs, scope potential solutions, and identify opportunities for growth.
• Create technical proposals, solution architectures, and presentations to support sales efforts and ensure alignment with customer expectations.
• Assist in responding to RFPs/RFIs by providing accurate technical input and aligning solutions to client requirements.
• Demonstrate AWS capabilities through POCs (Proof of Concepts) and technical demonstrations to help customers evaluate the proposed solutions.

• Customer Engagement and Relationship Management

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  Build and maintain strong relationships with key customer stakeholders, serving as a trusted advisor on data platform initiatives.
• Lead discovery workshops to understand customer requirements, KPIs, and technical constraints.

• Project Leadership and Delivery

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  Oversee the end-to-end implementation of AWS-based data platforms, coordinating with engineering teams to ensure successful delivery.
• Manage technical risks and develop mitigation strategies to address potential challenges.

• Innovation and Best Practices

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  Stay abreast of the latest developments in AWS, Databricks, data engineering, and cloud technologies.
• Develop and promote best practices in data platform architecture, data pipelines, and data governance.

• Cross-Functional Collaboration

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  Collaborate with AI/ML teams to integrate advanced analytics and machine learning capabilities into AWS and other cloud platforms.
• Work with DevOps teams to implement CI/CD pipelines and automation for data workflows.

• Mentorship and Knowledge Sharing

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  Mentor junior architects and engineers, fostering a culture of continuous learning and professional development.
• Contribute to knowledge-sharing initiatives, including writing technical blogs, case studies, and presenting at industry events.

• Governance, Compliance, and Security

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  Ensure that AWS-based data platform solutions comply with relevant security standards and regulations.
• Implement data governance frameworks to maintain data quality and integrity.

Requirements:

• Education

• Experience

• 
  Minimum of 8 years of experience in data solution architecture, with at least 3 years focused on AWS.
• Proven experience in designing and implementing large-scale data engineering solutions on AWS.
• Experience with Databricks is a plus.

• Technical Skills

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  Deep expertise in AWS platform services, including 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.

• Certifications

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  AWS Certified Solutions Architect – Professional or similar AWS certifications are a plus.

• Soft Skills

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  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:

• Certifications in Databricks.
• Experience with AWS Migration Acceleration Programs (MAP).
• Experience with AI/ML integration in data platforms.
• Contributions to open-source projects or active participation in the data engineering community.