Databricks Engineer

Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Databricks Engineer you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project Delivery Model (PDM) is a talent model that is tailored specifically for long-term, onsite and/or remote client service delivery.

Recruiting for this role ends on 06/30/2026.

Work you'll do

As a Databricks Engineer on the AI & Data team, you will be responsible for...

• Build, configure, and support Databricks environments across Microsoft Azure, Amazon Web Services, and Google Cloud Platform, including integrations
• Develop and maintain Databricks notebooks, jobs, workflows, and pipelines for data and analytics solutions
• Translate approved technical designs into implementation tasks and document configuration, dependencies, and deployment steps
• Support platform configuration, infrastructure setup, testing, and deployment readiness across environments
• Work with delivery teams, data science teams, and client stakeholders to troubleshoot issues, support releases, and maintain platform performance

A successful candidate would possess these skills:

• Ability to work independently and collaborate as part of a team
• Effective written and verbal communication skills
• Meticulous attention to detail and quality of work product
• Ability to build and sustain professional relationships
• Ability to lead projects or workstreams
• Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
• Strong interpersonal skills and professional demeanor
• Ability to meet deadlines
• Ability to provide clear guidance to others

The team

AI & Engineering leverages engineering capabilities to build, deploy, and operate sector-focused solutions across software, data, AI, network, and hybrid cloud infrastructure. The practice helps clients modernize technology and data platforms and apply engineering to mission-critical operations. Our AI & Data practice designs, develops, and operates data and AI platforms, products, insights, and services to help organizations scale their analytics and AI capabilities.

Qualifications

Required:

• Bachelor's degree preferably in Computer Science, Information Technology, Computer Engineering, or equivalent experience
• 5+ years of experience with Databricks platform implementation, configuration, or development
• Experience building Databricks environments in Microsoft Azure, Amazon Web Services, or Google Cloud Platform, including integrations
• Experience developing or supporting extract, transform, and load (ETL) pipelines in Databricks
• Experience with Databricks workspace administration, machine learning operations (MLOps), or infrastructure setup
• Limited immigration sponsorship may be available.
• Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve.

Preferred:

• Experience in consulting, including experience serving healthcare industry clients

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $121,400 to $143,600.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.