The Senior Data Solutions Architect will design, implement, and lead large-scale data solutions on AWS, fostering customer engagement and promoting best practices in data engineering.
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
- Solution Architecture and Design
- Pre-Sales Activities
- Customer Engagement and Relationship Management
- Project Leadership and Delivery
- Innovation and Best Practices
- Cross-Functional Collaboration
- Mentorship and Knowledge Sharing
- Governance, Compliance, and Security
- 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.
Requirements:
- Education
- Experience
- Technical Skills
- Certifications
- Soft Skills
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.
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.
Top Skills
AWS
Aws Msk
Databricks
Ec2
Eks
Emr
Glue
Lambda
Python
Redshift
S3
Scala
Snowflake
SQL
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