Solutions Architect - Public Sector
Customer-facing solutions architect helping public sector clients evaluate, design, and implement Databricks data and AI solutions. Requires 7+ years in pre-sales architecture or consulting, distributed data systems expertise, public cloud experience, and a Top Secret clearance.
About the job
Responsibilities
- Partner with the sales team to help customers understand how Databricks can solve their business problems.
- Provide technical leadership as customers evaluate and adopt Databricks.
- Consult on big data architecture, implement proofs of concept for strategic customer projects, support data science and machine learning projects, and validate integrations with cloud services and third-party applications.
- Build and present reference architectures, how-to guides, and demo applications for customers.
- Promote Databricks-inspired open-source projects across developer communities through meetups, conferences, and webinars.
- Travel to customers in the region.
Requirements
- 7+ years of experience in a customer-facing pre-sales, technical architecture, or consulting role.
- Experience designing and architecting distributed data systems.
- Proficiency in and debugging experience with at least one of Python, Scala, Java, SQL, or R.
- Experience supporting public sector clients.
- Experience building solutions with public cloud providers such as AWS, Azure, or GCP.
- Expertise in at least one of the following areas:
- Data engineering technologies, such as Spark, Hadoop, or Kafka
- Data warehousing, such as SQL, OLTP, OLAP, or DSS
- Data science and machine learning technologies, such as pandas, scikit-learn, or HPO
- Top Secret security clearance required.
Nice-to-Have
- Degree in a quantitative discipline, such as Computer Science, Applied Mathematics, or Operations Research.
Compensation
- Annual pay range: $180,000-$247,500 USD.
- Total compensation may also include an annual performance bonus, equity, and benefits.
Skills
Databricks, Spark, MLflow, Delta Lake, Python, Scala, Java, SQL, R, AWS, Azure, GCP, Hadoop, Kafka, pandas
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