Resident Solutions Architect - Manufacturing
Databricks6 months ago
Base Salary
$181k - $248k/yr
Responsibilities
- Deliver customer technical projects involving reference architectures, how-to documentation, and productionization of customer use cases.
- Scope professional services work with engagement managers and customers.
- Guide strategic customers through big data projects, third-party migrations, and end-to-end design, build, and deployment of data and AI applications.
- Consult on architecture and design and implement customer projects to support Databricks evaluation, adoption, and successful use.
- Provide escalated support for customer operational issues.
- Collaborate with technical, project management, architecture, and customer teams to deliver engagement components according to customer needs.
- Work with Engineering and Customer Support to provide product and implementation feedback and resolve engagement-specific issues.
Requirements
- At least 6 years of experience in data engineering, data platforms, and analytics.
- Ability to write code in Python or Scala.
- Working knowledge of at least two cloud ecosystems among AWS, Azure, and GCP, with expertise in at least one.
- Deep experience with distributed computing using Apache Spark and knowledge of Spark runtime internals.
- Familiarity with CI/CD for production deployments and working knowledge of MLOps.
- Experience designing and deploying performant end-to-end data architectures.
- Experience delivering technical projects, including managing scope and timelines.
- Strong documentation and whiteboarding skills.
- Experience working with clients and managing conflicts.
- Ability to build technical solutions supporting the deployment and integration of Databricks-based solutions.
- Ability to travel up to 30% when needed.
Benefits
- Comprehensive benefits and perks, with region-specific details available through Databricks' benefits site.
Tech Stack
Categories
Data EngineeringSolutions Engineering
About Databricks
Databricks builds a cloud-based data and AI platform centered on the lakehouse architecture, combining data engineering, analytics, and machine learning with Apache Spark, Delta Lake, and MLflow. It sells subscriptions and cloud services to enterprises that need to unify data pipelines and develop large-scale AI and analytics. Founded in 2013 by the creators of Apache Spark and headquartered in San Francisco, the company is privately held and serves organizations across many industries.