Senior Solutions Engineer – Digital Native Business, Named Accounts

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Logo of Databricks

Databricks

1001 - 5000 employees

Founded 2013

🤖 Artificial Intelligence

🏢 Enterprise

☁️ SaaS

💰 $1.6G Series H on 2021-08

Artificial Intelligence • Enterprise • SaaS

Databricks is a data and AI company that provides a unified platform for data engineering, machine learning, and analytics. It focuses on optimizing big data processing and helps organizations leverage Apache Spark to deliver deeper insights and powerful data-driven applications. Databricks also offers robust tools and seamless integration for machine learning operations.

📋 Description

• Shape the future of the big data landscape by working with sophisticated data engineering and data science teams • Collaborate with existing Digital Native Business customers, product teams, and the broader customer-facing team to develop architectures and solutions using Databricks’ platform and APIs • Guide customers through the competitive landscape, best practices, and implementation, while developing technical champions • Partner with the sales team and provide technical leadership to help customers understand how Databricks can solve business problems • Consult on Big Data architectures • Implement proofs of concept for strategic data engineering, data science, machine learning, and SQL analysis projects • Validate integrations with cloud services, home-grown tools, and third-party applications • Collaborate with fellow Solutions Architects to support users and colleagues • Become an expert in, promote, and recruit contributors for Databricks-inspired open-source projects including Spark, Delta Lake, and MLflow • Report to the Field Engineering Manager

🎯 Requirements

• 3+ years in data engineering, data science, technical architecture, or a similar pre-sales/consulting role • Experience building distributed data systems • Comfortable programming in and debugging 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 data science and machine learning technologies such as pandas, scikit-learn, PyTorch, or TensorFlow • Available to travel to customers in the candidate’s region • Degree in a quantitative discipline is desired, not required • Databricks Certification is nice to have, not required

🏖️ Benefits

• Eligibility for annual performance bonus • Equity • Comprehensive benefits and perks; specific regional benefits are provided via the employer’s benefits details

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