Full-Time

Big Data Solutions Architect

Posted on 12/20/2024

Databricks

Databricks

5,001-10,000 employees

Unified data platform for analytics and AI

Data & Analytics
Enterprise Software
AI & Machine Learning

Senior

London, UK

Travel to customers 30% of the time.

Category
Solution Engineering
Sales & Solution Engineering
Required Skills
Microsoft Azure
Python
Apache Spark
AWS
Scala
Databricks
Data Analysis
Google Cloud Platform
Requirements
  • Proficient in data engineering, data platforms, and analytics with a strong track record of successful projects and in-depth knowledge of industry best practices
  • Comfortable writing code in either Python or Scala
  • Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
  • Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
  • Familiarity with CI/CD for production deployments
  • Working knowledge of MLOps
  • Design and deployment of performant end-to-end data architectures
  • Experience with technical project delivery - managing scope and timelines
  • Documentation and white-boarding skills
  • Experience working with clients and managing conflicts
  • Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects
  • Travel to customers 30% of the time
  • Databricks Certification
Responsibilities
  • You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
  • Work with engagement managers to scope variety of professional services work with input from the customer
  • Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
  • Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks
  • Provide an escalated level of support for customer operational issues
  • You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs
  • Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues

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. The goal of Databricks is to empower organizations to leverage their data effectively for better decision-making.

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

  • Increased demand for data lakehouse solutions boosts Databricks' market potential.
  • Growing interest in open-source tools aligns with Databricks' acquisition of Tabular.
  • Expansion of AI applications in key sectors enhances Databricks' client base.

What critics are saying

  • Increased competition from companies like Snowflake threatens Databricks' market share.
  • Integration challenges with Tabular could lead to operational inefficiencies.
  • Rapid AI model development may attract ethical and regulatory scrutiny.

What makes Databricks unique

  • Databricks offers a unified platform combining data lakes and warehouses, known as lakehouse.
  • The platform supports collaborative data science and machine learning workflows.
  • Databricks integrates with various cloud services for 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