Data Solutions Architect (AWS)

Provectus, is a leading AI consultancy and solutions provider specializing in Data Engineering and Machine Learning. With a focus on helping businesses unlock the power of their data, we leverage the latest technologies to build innovative data platforms that drive results. Our Data Engineering team consists of top-tier professionals who design, implement, and optimize scalable, data-driven architectures for clients across various industries.

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.

Responsibilities:

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Strategic Technical Leadership:

• Lead high-impact customer engagements focused on AWS Data Platform solutions.
• Define and drive technical strategies that align AWS capabilities with customer objectives, incorporating Databricks, GCP, or Azure where appropriate.

Solution Architecture and Design:

• Architect and design scalable data platforms using AWS, ensuring optimal performance, security, and cost-efficiency.
• Integrate AWS services with other solutions (Databricks, Snowflake, GCP, or Azure) as needed, selecting the right technologies and tools to meet customer needs.
• Develop and maintain comprehensive architectural documentation aligned with organizational technical standards.

Pre-Sales Activities:

• Partner with the sales team, providing technical expertise to position AWS-based data solutions effectively.
• Participate in customer meetings to assess technical needs, scope solutions, and identify growth opportunities.
• Create technical proposals, solution architectures, and presentations to support sales efforts and align with customer expectations.
• Assist in responding to RFPs/RFIs with accurate technical input and align solutions to client requirements.
• Demonstrate AWS capabilities through POCs and technical demonstrations to showcase proposed solutions.

Customer Engagement and Relationship Management:

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

Project Leadership and Delivery:

• 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.

Innovation and Best Practices:

• Stay up-to-date with the latest developments in AWS, Databricks, GCP, Azure, and cloud technologies.
• Develop and promote best practices in data platform architecture, data pipelines, and data governance.

Cross-Functional Collaboration:

• 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:

• Mentor junior architects and engineers, fostering a culture of continuous learning and professional development.
• Contribute to knowledge-sharing initiatives through technical blogs, case studies, and industry event presentations.

Governance, Compliance, and Security:

• 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:

• Experience in data solution architecture.
• Proven experience in designing and implementing large-scale data engineering solutions on AWS.
• Experience with Databricks, GCP, or Azure solutions is required.
• 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 in data engineering.
• AWS Certified Solutions Architect – Professional (or similar) is required.
• Excellent communication and presentation skills, with the ability to convey 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:

• Experience in the Healthcare and Biotech domains.
• Certifications in Databricks, GCP, or Azure.
• Experience with AWS Migration Acceleration Programs (MAP).
• Experience with AI/ML integration in data platforms.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Contributions to open-source projects or active participation in the data engineering community.