Full-Time

Solutions Architect

Confirmed live in the last 24 hours

Databricks

Databricks

5,001-10,000 employees

Unified data platform for analytics and AI

Data & Analytics
Enterprise Software
AI & Machine Learning

Senior

Toronto, ON, Canada + 1 more

More locations: Remote in Canada

Remote candidates in other locations in eastern Canada are welcome.

Category
Solution Engineering
Sales & Solution Engineering
Required Skills
Scikit-learn
Python
Data Science
R
Apache Spark
SQL
Machine Learning
Apache Kafka
Java
Pandas
Scala
Hadoop
Databricks

You match the following Databricks's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • 5+ years in a customer-facing pre-sales, technical architecture, or consulting role with expertise in at least one of the following technologies: Big data engineering (Ex: Spark, Hadoop, Kafka), Data Warehousing & ETL (Ex: SQL, OLTP/OLAP/DSS), Data Science and Machine Learning (Ex: pandas, scikit-learn, HPO), Data Applications (Ex: Logs Analysis, Threat Detection, Real-time Systems Monitoring, Risk Analysis and more)
  • Experience translating a customer's business needs to technology solutions, including establishing buy-in with essential customer stakeholders at all levels of the business.
  • Experienced at designing, architecting, and presenting data systems for customers and managing the delivery of production solutions of those data architectures.
  • Fluent in SQL and database technology.
  • Debug and development experience in at least one of the following languages: Python, Scala, Java, or R.
Responsibilities
  • Work with Sales and other essential partners to develop account strategies for your assigned accounts to grow their usage of the platform.
  • Establish the Databricks Lakehouse architecture as the standard data architecture for customers through excellent technical account planning.
  • Build and present reference architectures and demo applications for prospects to help them understand how Databricks can be used to achieve their goals to land new users and use cases.
  • Capture the technical win by consulting on big data architectures, data engineering pipelines, and data science/machine learning projects; prove out the Databricks technology for strategic customer projects; and validate integrations with cloud services and other 3rd party applications.
  • Become an expert in, and promote Databricks inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars.
Desired Qualifications
  • Built solutions with public cloud providers such as AWS, Azure, or GCP
  • Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)

Databricks provides a platform that combines the features of data lakes and data warehouses, referred to as lakehouse architecture. This platform allows organizations to efficiently manage, analyze, and gain insights from their data. It caters to a diverse clientele, including data engineers, data scientists, and business analysts in sectors like finance, healthcare, and technology. Databricks streamlines data ingestion, management, and analysis through automated ETL processes, secure data sharing, and high-performance analytics. Additionally, it supports machine learning and AI workloads, enabling users to build and deploy models at scale. The company operates on a subscription-based model, generating revenue from platform access and professional services. Databricks aims to enhance data management and analytics for its users, making it easier to derive valuable insights from their data.

Company Stage

Debt Financing

Total Funding

$13.6B

Headquarters

San Francisco, California

Founded

2013

Growth & Insights
Headcount

6 month growth

0%

1 year growth

1%

2 year growth

0%
Simplify Jobs

Simplify's Take

What believers are saying

  • Databricks raised $15 billion in Series J funding, boosting AI product development.
  • The company plans global expansion, supported by strategic investors like Meta.
  • Increased demand for real-time analytics aligns with Databricks' platform capabilities.

What critics are saying

  • Increased competition from Snowflake may impact Databricks' market share.
  • Rapid AI advancements could outpace Databricks' feature integration.
  • Potential overvaluation concerns with a $62 billion valuation may attract scrutiny.

What makes Databricks unique

  • Databricks' lakehouse architecture combines data lakes and warehouses for efficient data management.
  • The platform supports collaborative data science and machine learning workflows at scale.
  • Databricks integrates seamlessly with various cloud services for enhanced data management.

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Benefits

Extended health care including dental and vision

Life/AD&D and disability coverage

Equity awards

Flexible Vacation

Gym reimbursement

Annual personal development fund

Work headphones reimbursement

Employee Assistance Program (EAP)

Business travel accident insurance

Paid Parental Leave