Big Data Solutions Architect

As a Big Data Solutions Architect (Resident Solutions Architect) in our Professional Services team, you will work with clients on short to medium-term customer engagements to address their big data challenges using the Databricks Data Intelligence Platform. You will provide data engineering, data science, and cloud technology projects, which include integrating with client systems, training, and other technical tasks to help customers maximize the value of their data. RSAs are billable and are skilled at completing projects according to specifications while delivering excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

1. Work on a variety of impactful customer technical projects, including designing and building reference architectures, creating how-to guides, and productionalizing customer use cases.
2. Collaborate with engagement managers to scope professional services work with input from the customer.
3. Guide strategic customers through implementing transformational big data projects and 3rd party migrations, including end-to-end design, build, and deployment of industry-leading big data and AI applications.
4. Consult on architecture and design; bootstrap or implement customer projects, leading to successful understanding, evaluation, and adoption of Databricks.
5. Provide escalated support for customer operational issues.
6. Coordinate with the Databricks technical team, Project Manager, Architect, and Customer team to ensure technical components of engagements meet customer needs.
7. Work with Engineering and Support to provide product and implementation feedback and guide rapid resolution of engagement-specific issues.

What we look for:

1. Proficiency in data engineering, data platforms, and analytics with a strong track record of successful projects and industry best practices.
2. Ability to write code in Python or Scala.
3. Working knowledge of two or more cloud ecosystems (AWS, Azure, GCP), with expertise in at least one.
4. Deep experience with distributed computing using Apache Spark and knowledge of Spark runtime internals.
5. Familiarity with CI/CD pipelines for production deployments.
6. Knowledge of MLOps.
7. Experience in designing and deploying performant end-to-end data architectures.
8. Experience managing technical project delivery, including scope and timelines.
9. Strong documentation and whiteboarding skills.
10. Experience working with clients and managing conflicts.
11. Skills supporting deployment and integration of Databricks-based solutions for customer projects.

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