Simplify Logo

Full-Time

Solutions Architect

AI/ML

Confirmed live in the last 24 hours

Snowflake

Snowflake

5,001-10,000 employees

Data Cloud platform for data warehousing

Data & Analytics
Consulting
Enterprise Software
AI & Machine Learning

Senior, Expert

Remote in USA

Category
Solution Engineering
Sales & Solution Engineering
Required Skills
Microsoft Azure
Python
Sales
Jupyter
Data Science
Tensorflow
Pytorch
SQL
Java
AWS
Pandas
Scala
Marketing
Google Cloud Platform
Requirements
  • University degree in data science, computer science, engineering, mathematics or related fields, or equivalent experience.
  • Minimum 6 years experience working with customers in a pre-sales or post-sales technical role.
  • Outstanding skills presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos.
  • Thorough understanding of the complete Data Science life-cycle including feature engineering, model development, model deployment and model management.
  • Strong understanding of MLOps, coupled with technologies and methodologies for deploying and monitoring models.
  • Experience and understanding of at least one public cloud platform (AWS, Azure or GCP).
  • Experience with at least one Data Science tool such as AWS Sagemaker, AzureML, Dataiku, Datarobot, H2O, and Jupyter Notebooks.
  • Hands-on scripting experience with SQL and at least one of the following; Python, Java or Scala.
  • Experience with libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn or similar.
Responsibilities
  • Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload.
  • Provide customers with best practices and advise as it relates to Data Science workloads on Snowflake.
  • Build, deploy and ML pipelines using Snowflake features and/or Snowflake ecosystem partner tools based on customer requirements.
  • Work hands-on where needed using SQL, Python, Java and/or Scala to build POCs that demonstrate implementation techniques and best practices on Snowflake technology within the Data Science workload.
  • Follow best practices, including ensuring knowledge transfer so that customers are properly enabled and are able to extend the capabilities of Snowflake on their own.
  • Maintain deep understanding of competitive and complementary technologies and vendors within the AI/ML space, and how to position Snowflake in relation to them.
  • Work with System Integrator consultants at a deep technical level to successfully position and deploy Snowflake in customer environments.
  • Provide guidance on how to resolve customer-specific technical challenges.
  • Support other members of the Professional Services team develop their expertise.
  • Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake’s products and marketing.

Snowflake offers a Data Cloud platform for data warehousing, data lakes, and data application development, enabling secure sharing of governed data across multiple public clouds. The platform supports diverse analytic workloads with near-unlimited scale and performance.

Company Stage

IPO

Total Funding

$2.5B

Headquarters

San Mateo, California

Founded

2012

Growth & Insights
Headcount

6 month growth

9%

1 year growth

7%

2 year growth

43%
Simplify Jobs

Simplify's Take

What believers are saying

  • Snowflake's continuous innovation and feature expansion, as seen in their Data Cloud World Tour, promise robust career growth opportunities.
  • The company's strategic investments and acquisitions indicate strong financial health and a commitment to staying at the forefront of data technology.
  • Collaborations with companies like Solaris and Omnata highlight Snowflake's influence and integration capabilities across various industries.

What critics are saying

  • The rapid pace of acquisitions and integrations may lead to operational challenges and cultural misalignment.
  • Intense competition in the cloud data platform market from giants like AWS and Google Cloud could pressure Snowflake's market share.

What makes Snowflake unique

  • Snowflake's focus on democratizing data access and analytics sets it apart from traditional data platforms.
  • Strategic investments in AI-driven startups like Metaplane enhance Snowflake's data quality and reliability, providing a competitive edge.
  • Acquisitions such as Samooha and Ponder expand Snowflake's capabilities in data clean rooms and Python integration, respectively.

Benefits

We've got your back - We offer comprehensive health insurance plans, health savings accounts, robust retirement plans, and generous life and disability insurance.

A Balanced Lifestyle - All Snowflakes have access to our weekly online lunch and learns, virtual workout classes, and ergonomic work-from-home equipment. We offer on-demand mental health and wellness programs to support our employees and their families.

Your People Matter - Help offset the cost of growing your family with our fertility benefits and family planning resources. Count on our generous time-off and various leave plans for you to rest, refuel, and sustain a great work-life balance.

Global Snowflake Team - No matter where you are in the world, we will get you connected and supported with a work-from-home setup.

Treat Yourself - Personalize your Snowflake benefits by tapping into our employee discounts and pre-tax selections.

Invest In Your Future - Eligible employees enjoy new hire equity, Employee Stock Purchase Plan (ESPP), and a quarterly bonus or commission program.