Senior Data Solutions Architect with AWS

Join us if you have the same passion for making products using AI/ML technologies, cloud services, and data engineering.

As a Data Solutions Architect, you will lead the design, architecture, and implementation of large-scale data solutions for our clients. You will act as a strategic technical leader, collaborating with cross-functional teams to deliver innovative data platforms that drive business value.

- 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.

- 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.

- 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.

- 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.

- 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.

- 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.

- 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.

- 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.

- Ensure that AWS-based data platform solutions comply with relevant security standards and regulations.

- Implement data governance frameworks to maintain data quality and integrity.

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

- 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.

- 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.

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

- 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.