Data Science Architect - Professional Services
About this role
CSQ227R186
As a Data Science Architect (internal title - Resident Solutions Architect) in our Professional Services team, you will work with customers on short to medium-term engagements to solve their toughest machine learning and AI challenges using the Databricks platform.You will deliver data science, data engineering and cloud architectural design projects as a trusted advisor to our customers, ensuring that they get the most value out of their data. RSAs facilitate safe, scalable application of the Databricks platform across many verticals, aligning to customer business objectives. You will report to the regional Manager/Lead.
The impact you will have:
You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
Work with engagement managers to scope variety of professional services work with input from the customer
Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
Provide an escalated level of support for customer operational issues.
You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.
What we look for (the more, the better!):
Proficient in data science, common machine learning frameworks (scikit-learn, PyTorch, TensorFlow, etc.), and analytics with a strong track record of delivering successful projects with in-depth knowledge of industry best practices.
Experience of productionising and optimising machine learning projects, with a knowledge of MLOps principles and how to apply them.
Experience with distributed computing with Apache Sparkâ„¢ and knowledge of Spark runtime internals
Experience in data engineering, data platforms & analytics
Comfortable writing code in either Python or Scala
Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
Familiarity with CI/CD for production deployments
Design and deployment of performant end-to-end data architectures
Experience with technical project delivery - managing scope and timelines.
Documentation and white-boarding skills.
Experience working with clients and managing conflicts.
Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
Travel to customers 10% of the time
[Preferred] Databricks Certification but not essential
Responsibilities
- You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
- Work with engagement managers to scope variety of professional services work with input from the customer
- Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
- Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
- Provide an escalated level of support for customer operational issues.
- You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
- Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.
- Proficient in data science, common machine learning frameworks (scikit-learn, PyTorch, TensorFlow, etc.), and analytics with a strong track record of delivering successful projects with in-depth knowledge of industry best practices.
- Experience of productionising and optimising machine learning projects, with a knowledge of MLOps principles and how to apply them.
- Experience with distributed computing with Apache Sparkâ„¢ and knowledge of Spark runtime internals
- Experience in data engineering, data platforms & analytics
Requirements
- Comfortable writing code in either Python or Scala
- Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
- Familiarity with CI/CD for production deployments
- Design and deployment of performant end-to-end data architectures
- Experience with technical project delivery - managing scope and timelines.
- Documentation and white-boarding skills.
- Experience working with clients and managing conflicts.
- Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
- Travel to customers 10% of the time
- [Preferred] Databricks Certification but not essential
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.