Senior Data Solutions Architect (AWS)

Posted 22 Days Ago
Be an Early Applicant
Hiring Remotely in Serbia
Remote
5-7 Years Experience
Artificial Intelligence • Information Technology • Consulting
The Role
Lead the design, architecture, and implementation of large-scale data solutions for clients, collaborating with cross-functional teams to deliver innovative data platforms that drive business value.
Summary Generated by Built In

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.

Top Skills

AWS
The Company
HQ: Palo Alto, CA
572 Employees
On-site Workplace
Year Founded: 2010

What We Do

Provectus is an Artificial Intelligence consultancy and solutions provider, helping businesses achieve their objectives through AI.

We are recognized by industry think tanks as a leading provider of AI solutions in specific business domains, driven by sophisticated IT service management and tech innovation. Provectus is a value driver and a trusted partner for our clients and employees.

Provectus is an AWS Premier Consulting Partner with competencies in Data & Analytics, DevOps, and Machine Learning. We design and build AI solutions for industry-specific use cases, Data and Machine Learning foundation, Cloud transformation, and DevOps adoption.

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