Databricks Engineer

As a databricks engineer, you will help design, build, and support data management solutions that enable reliable, scalable, and secure use of data across business and technology functions. In this role, you will collaborate with cross-functional stakeholders to develop data pipelines, improve data quality, and support data governance and integration efforts. The ideal candidate brings hands-on experience in data engineering and the ability to manage multiple priorities in a dynamic environment.

Work you'll do

As a databricks engineer on the team, you will be responsible for…

• Design, build, test, and maintain data pipelines and data integration solutions
• Support data modeling, transformation, and storage processes across structured and unstructured data sources
• Monitor data workflows, troubleshoot issues, and implement fixes to improve reliability and performance
• Collaborate with business, analytics, and technology teams to define data requirements and support delivery priorities
• Apply data quality, metadata, and governance standards across data assets and processes

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

Our team supports the design, development, and delivery of data management solutions that help organizations improve the quality, accessibility, and usability of their data. We work across functions to enable trusted data for reporting, analytics, operations, and strategic decision-making. Team members collaborate closely with stakeholders to solve complex data challenges in a fast-paced, client-service environment.

Qualifications

Required:

• Bachelor's degree required
• 2+ years of experience in data engineering, data integration, or data management, including 3+ years of experience with Structured Query Language (SQL)
• 2+ years of experience building or supporting extract, transform, and load (ETL) or extract, load, and transform (ELT) pipelines
• 2+ years of experience with Python and PySpark
• 1+ years of experience with Databricks and cloud-based data platforms, including data pipeline development and data transformation
• Ability to travel 10-15%, on average, based on the work you do and the clients and industries/sectors you serve.
• Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred:

• Experience with data warehousing concepts and dimensional data modeling
• Experience with data quality, metadata, or data governance processes
• Experience working with application programming interfaces (APIs) and system integrations
• Experience supporting Agile delivery teams
• Experience in a professional services environment

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 $97,700 to $162,800.

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.