Provectus, 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:

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:

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.