Databricks

Sr. Solutions Engineer

Databricks
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3 months ago
Toronto, CanadaSenior

Responsibilities

  • Serve as the main technical voice for multiple clients.
  • Define and direct technical strategy for major enterprise accounts in partnership with the Enterprise Account Executive.
  • Guide customers through evaluating and adopting Databricks as part of their strategic transformation.
  • Implement account technical strategy and maintain a close understanding of the strategy.
  • Build a network of technical champions within customer accounts.
  • Align customer technical strategies around Databricks solutions.
  • Collaborate with sales teams and technical peers to drive business outcomes for clients.

Requirements

  • Demonstrated success establishing and leading virtual teams within customer accounts.
  • Experience working with very large accounts exceeding $1 million ARR and global enterprises.
  • Ability to build relationships with executives, influencers, and important decision-makers.
  • Ability to present a compelling point of view that guides customers toward successful outcomes.
  • Technical knowledge of big data, data science, and cloud platforms including Azure and AWS.
  • Experience with data-driven business transformation and driving organizational change through data.
  • Production programming experience in Python, R, Scala, or Java.
  • Databricks, Snowflake, AWS, or Azure certification is preferred.

Benefits

  • Comprehensive benefits and perks are offered; specific regional details are provided through the employer.
  • The role is located in Toronto, Ontario, Canada.

Tech Stack

Apache SparkAWSAzureDatabricksJavaMLflowPythonRScalaSnowflake

Categories

Solutions Engineering
Databricks

About Databricks

10,000+ employees

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.

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