Full-Time

Product Specialist

Mosaic AI

Posted on 9/6/2024

Databricks

Databricks

5,001-10,000 employees

Unified data platform for analytics and AI

Data & Analytics
Enterprise Software
AI & Machine Learning

Senior

London, UK

Category
Applied Machine Learning
AI Research
AI & Machine Learning
Required Skills
Microsoft Azure
Python
Apache Spark
SQL
Databricks
Data Analysis
Requirements
  • Experience in designing and delivering cloud-based Data Warehousing Solutions in a client or customer environment
  • Ability to advise customers in Data Warehousing architecture: Prepare Databricks stakeholders for internal conversations and communicate directly, including anticipating blockers and address them before they become an issue
  • Cross-Cloud Expertise: Help customers build a multi-cloud analytics ecosystem with Databricks at the centre and provide solutions for customers looking for disaster recovery, fault tolerance and backup
  • Certification and/or demonstrated competence in the Azure ecosystem
  • Demonstrated competence in the Lakehouse architecture including hands-on experience with Apache Spark, Python and SQL
  • Excellent communication skills; both written and verbal
  • Experience in pre-sales selling highly desired
Responsibilities
  • Deliver thought leadership in Mosaic AI best practices for the Databricks Data Intelligence Platform in the form of blogs, webinars, how to guides and technical know-how to the EMEA technical community and beyond.
  • Working with sales and FE leaders drive adoption of Mosaic AI across EMEA
  • Provide a strong, informed, and data-driven perspective in conversations with the Product and Engineering teams to influence our product strategy and priorities in how customers can and should bring Databricks into their Data strategies.
  • Provide guidance and oversight for large-scale enterprise Mosaic AI competitive scenarios, serving as a trusted technical advisor to senior tech leads and executives
  • Act as the level three point of escalation on the toughest technical challenges in the field that customers face to drive customer success.
  • Build and manage an SME group in EMEA field-engineering around Mosaic AI
  • Provide key messaging and approaches to ensure the EMEA technical field is prepared for competitive conversations

Databricks provides a unified platform that combines data lakes and data warehouses, known as lakehouse architecture, allowing organizations to manage, analyze, and gain insights from their data effectively. The platform features automated ETL processes, secure data sharing, and high-performance analytics, making it suitable for data engineers, data scientists, and business analysts across various industries like finance, healthcare, and technology. Unlike its competitors, Databricks focuses on integrating machine learning and AI workloads, enabling users to build and deploy models at scale. The company's goal is to streamline data management and analytics through a subscription-based service, ensuring clients can efficiently access and utilize their data.

Company Stage

Growth Equity (Venture Capital)

Total Funding

$13.6B

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

  • Databricks raised $10 billion for AI product development and global expansion in 2023.
  • The company has over 500 customers with $1 million+ annual run rates, indicating strong market presence.
  • Databricks' expansion into Saudi Arabia aligns with Vision 2030, enhancing its Middle East presence.

What critics are saying

  • Increased competition from Snowflake could impact Databricks' market share in the lakehouse sector.
  • Integration challenges with acquisitions like Tabular may disrupt operations and delay product rollouts.
  • Expansion into new markets like Saudi Arabia may expose Databricks to geopolitical and regulatory risks.

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 seamlessly with various cloud services, facilitating efficient 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

INACTIVE