Sr. Solutions Engineer - Digital Native Business, Named Accounts
Databricks2 months ago
Base Salary
$152k - $209k/yr
Responsibilities
- Partner with the sales team to provide technical leadership and explain how Databricks can solve customer business problems.
- Consult on big data architectures and implement proofs of concept across data engineering, data science, machine learning, and SQL analysis workflows.
- Validate integrations with cloud services, internal tools, and third-party applications.
- Collaborate with Solutions Architects and support customers and users.
- Guide customers through competitive landscapes, best practices, and implementation while developing technical champions.
- Become an expert in, promote, and recruit contributors for Databricks-inspired open-source projects including Spark, Delta Lake, and MLflow.
Requirements
- At least 3 years of experience in data engineering, data science, technical architecture, or a similar pre-sales or consulting role.
- Experience building distributed data systems.
- Ability to program in and debug Python and SQL.
- Experience building solutions with public cloud providers such as AWS, Azure, or GCP.
- Expertise in data engineering technologies such as Spark, Hadoop, or Kafka, or in data science and machine learning technologies such as pandas, scikit-learn, PyTorch, or TensorFlow.
- Availability to travel to customers in the candidate's region.
- A degree in a quantitative discipline such as Computer Science, Applied Mathematics, or Operations Research is desired.
- Databricks Certification is a nice-to-have qualification.
Benefits
- Remote role indicated by #LI-REMOTE.
- Travel to customers in the candidate's region is expected.
- Comprehensive benefits and perks are offered, with region-specific details available from Databricks.
Tech Stack
Apache HadoopApache KafkaApache SparkAWSAzureDatabricksGoogle Cloud PlatformMLflowPandasPythonPyTorchscikit-learnSQLTensorFlow
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.