Sr. Solutions Architect - Financial Services (Strategic Banking)
Databricks2 months ago
Base Salary
$219k - $301k/yr
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, execute proofs of concept, and validate integrations with cloud services and third-party applications.
- Build and present reference architectures, how-to materials, and application demonstrations for customers.
- Promote Apache Spark, Delta Lake, MLflow, and Unity Catalog through developer communities, meetups, conferences, and webinars.
- Build customer relationships, cultivate champions, and establish trusted-advisor relationships.
- Travel to meet customers in the assigned territory.
Requirements
- 8+ years of customer-facing pre-sales or consulting experience, preferably solving data engineering and big-data analytical challenges.
- Experience designing and architecting distributed data systems.
- Programming and debugging experience in at least one of Python, SQL, Scala, Java, or R.
- Experience building solutions with public cloud providers such as AWS, Azure, or GCP.
- Experience with data engineering technologies such as Spark, Hadoop, or Kafka.
- Experience with data warehousing technologies such as SQL, OLTP, OLAP, or DSS.
- An undergraduate degree or higher in engineering or mathematics, such as Computer Science, Applied Mathematics, or Electrical Engineering.
- Experience with global system integrators, consulting organizations, financial services technology, or financial services data providers is a positive differentiator.
Benefits
- Comprehensive benefits and perks are offered; specific regional details are available from Databricks.
Tech Stack
Apache HadoopApache KafkaApache SparkAWSAzureDatabricksGoogle Cloud PlatformJavaMLflowPythonRScalaSQL
Categories
Solutions 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.