Senior Data Solutions Architect (AWS)
About project
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.