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: - Lead high-impact customer engagements focused on Databricks Data Platform solutions.
- Define and drive technical strategies that align Databricks capabilities with customer objectives.
- Architect scalable, secure, and reliable Databricks on AWS platforms, integrating with other AWS services and open-source technologies.
- Provide technical expertise during the pre-sales process, assisting with RFPs/RFIs and creating solution architectures.
- Oversee end-to-end implementation of data platforms, collaborating with cross-functional teams.
- Conduct POCs and technical demos to demonstrate Databricks capabilities.
- Build relationships with customer stakeholders, acting as a trusted advisor on data platform initiatives.
- Promote best practices in data governance, pipelines, and platform architecture.
- Mentor junior team members and contribute to knowledge-sharing efforts.
- Stay current on Databricks and cloud technology advancements.
Requirements: - Experience in data solution architecture.
- Proven experience in designing and implementing large-scale data engineering solutions on AWS.
- Deep expertise in the Databricks platform.
- Strong knowledge of AWS services such as 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.
- 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: - AWS Certified Solutions Architect – Professional or similar certifications.
- Databricks Certification (Databricks Certified Professional Data Engineer or equivalent certification).
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Experience with AI/ML integration in data platforms.
- Familiarity with data governance tools and practices.
- Contributions to open-source projects or active participation in the data engineering community.
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