Informacje o stanowisku

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:

1. Strategic Technical Leadership
2. Lead high-impact customer engagements focused on AWS Data Platform solutions
3. Define and drive technical strategies that align AWS capabilities with customer objectives, incorporating Databricks, GCP, or Azure where appropriate
4. Solution Architecture and Design
5. Architect and design scalable data platforms using AWS, ensuring optimal performance, security, and cost-efficiency
6. Integrate AWS services with other solutions (Databricks, Snowflake, GCP, or Azure) as needed, selecting the right technologies and tools to meet customer needs
7. Develop and maintain comprehensive architectural documentation aligned with organizational technical standards
8. Pre-Sales Activities
9. Partner with the sales team, providing technical expertise to position AWS-based data solutions effectively
10. Participate in customer meetings to assess technical needs, scope solutions, and identify growth opportunities
11. Create technical proposals, solution architectures, and presentations to support sales efforts and align with customer expectations
12. Assist in responding to RFPs/RFIs with accurate technical input and align solutions to client requirements
13. Demonstrate AWS capabilities through POCs and technical demonstrations to showcase proposed solutions
14. Customer Engagement and Relationship Management
15. Build and maintain strong relationships with key customer stakeholders, acting as a trusted advisor for data platform initiatives
16. Lead discovery workshops to understand customer requirements, KPIs, and technical constraints
17. Project Leadership and Delivery
18. Oversee the end-to-end implementation of AWS-based data platforms, coordinating with engineering teams to ensure successful delivery
19. Manage technical risks and develop mitigation strategies
20. Innovation and Best Practices
21. Stay up-to-date with the latest developments in AWS, Databricks, GCP, Azure, and cloud technologies
22. Develop and promote best practices in data platform architecture, data pipelines, and data governance
23. Cross-Functional Collaboration
24. Collaborate with AI/ML teams to integrate advanced analytics and machine learning capabilities into AWS and other cloud platforms
25. Work with DevOps teams to implement CI/CD pipelines and automation for data workflows
26. Mentorship and Knowledge Sharing
27. Mentor junior architects and engineers, fostering a culture of continuous learning and professional development
28. Contribute to knowledge-sharing initiatives through technical blogs, case studies, and industry event presentations
29. Governance, Compliance, and Security
30. Ensure that AWS-based data platform solutions comply with relevant security standards and regulations
31. Implement data governance frameworks to maintain data quality and integrity

1. Experience in data solution architecture
2. Proven experience in designing and implementing large-scale data engineering solutions on AWS
3. Experience with Databricks, GCP, or Azure solutions is required
4. Deep expertise in AWS platform services, including S3, EC2, Lambda, EMR, Glue, Redshift, AWS MSK, and EKS
5. Proficient in programming languages like Python, SQL, and Scala
6. Experience with data warehousing, ETL processes, and real-time data streaming
7. Familiarity with open-source technologies and tools in data engineering
8. AWS Certified Solutions Architect – Professional (or similar) is required
9. Excellent communication and presentation skills, with the ability to convey complex technical concepts to non-technical stakeholders
10. Strong leadership and project management skills
11. Ability to work collaboratively in a cross-functional team environment

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

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