Data Architect - AI & Automation

Company Description

LinkedIn is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed.

Join us to transform the way the world works.

Job Description

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.

This role is located in San Francisco or Sunnyvale. 

On the AI & Automation – Central Operations team, our mission is to leverage Data, AI and Advanced Analytics to deliver insights at scale and automate processes. We partner with LinkedIn’s Global Business Organization to find business needs for AI and Automation, scope and design new solutions, develop AI models and data pipelines, manage data products, automate processes, and deliver strategic insights. 

In this role, you will design, build, and maintain large-scale data foundations on Azure that power AI solutions to boost sales productivity. You will expand our Azure data ecosystem to support our analysis of customer interactions and better understand winning sales behaviors. By working with engineering and go-to-market teams, you’ll build data foundations that help improve employee training, deepen customer insights, and drive more successful deals.

Key Responsibilities

• Build and refine data pipelines using Azure Databricks and Azure Data Factory to move data securely and efficiently across systems with tools like Apache Airflow.

• Design and enhance scalable Azure architectures to support AI applications powered by large language models.

• Work with BI developers, data scientists, sales ops, and domain experts to convert business needs into robust technical solutions.

• Implement best practices for operations, including workflow orchestration, version control, CI/CD, and thorough documentation for quality, performance, and compliance.

• Act as a technical advisor and subject matter expert, offering guidance on design and process improvements that drive business impact.

Qualifications

Basic Qualifications

• Bachelor’s degree in Engineering, Computer Science, Data Science, or equivalent experience in a related technical field 

• 4+  years’ experience in a data engineering,  analytics engineering or a related role 

• 4+ years experience in Python and SQL.

• 2+  years’ experience with Databricks and Azure Data Factory.

• Proven ability to lead cross-functional projects and clearly communicate technical concepts to both technical and non-technical stakeholders.

Preferred Qualifications

• Master’s degree in Engineering, Computer Science, Data Science, or equivalent advanced experience.

• 2+ years’ experience implementing operational best practices (e.g., workflow orchestration, Git, CI/CD, Jira).

• Azure Solutions Architect certification or strong experience designing Azure platforms, including ML/AI tools.

• Experience optimizing queries on distributed systems, including API integrations.

• Experience working with unstructured data and large language models.

• Familiarity with SaaS business models and enterprise sales strategies is a plus.

• Knowledge of Java is a plus.

Suggested Skills:

• Databricks

•  Azure

• Python

• Airflow

•  AI/ML Workflows

LinkedIn is committed to fair and equitable compensation practices.   

The pay range for this role is $106,000-$174,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor.   

  The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits. 

Additional Information

Equal Opportunity Statement

LinkedIn is committed to di