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

Calgary, AB, Canada

Candidates in Calgary are preferred, but remote candidates from other locations in Canada are also welcome.

Category
Solution Engineering
Sales & Solution Engineering
Required Skills
Microsoft Azure
Python
Data Science
R
Apache Spark
SQL
Apache Kafka
Java
AWS
Pandas
Scala
Hadoop
Databricks
Google Cloud Platform
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.
  • [Desired] Built solutions with public cloud providers such as AWS, Azure, or GCP
  • [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
  • Travel to customers in your region up to 30% of the time.
Responsibilities
  • You will 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.
  • You will 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.

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 simplifies 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. Unlike many competitors, Databricks operates on a subscription-based model, generating revenue through platform access and professional services. The company's goal is to empower organizations to leverage their data effectively for better decision-making and insights.

Company Stage

Growth Equity (Venture Capital)

Total Funding

$3.9B

Headquarters

San Francisco, California

Founded

2013

Growth & Insights
Headcount

6 month growth

9%

1 year growth

38%

2 year growth

79%
Simplify Jobs

Simplify's Take

What believers are saying

  • Growing interest in generative AI models enhances Databricks' predictive capabilities and data processing.
  • Expansion of cloud-native data platforms supports scalable and resilient data architectures.
  • Increased collaboration with industry-specific partners tailors solutions for sectors like healthcare and finance.

What critics are saying

  • Increased competition from Voyage AI could threaten Databricks' market share in AI analytics.
  • Integration challenges from acquiring Tabular may impact Databricks' operational efficiency.
  • The DBRX generative AI model may not yield expected returns in a competitive market.

What makes Databricks unique

  • Databricks offers a unified platform combining data lakes and warehouses, known as lakehouse architecture.
  • The platform supports collaborative data science and machine learning workflows, enhancing team productivity.
  • Databricks integrates with various cloud services, facilitating seamless data management and analysis.

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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