Databricks Data Engineer II

Join Deloitte’s Core AI & Data practice and help organizations modernize data platforms, strengthen enterprise data foundations, and scale analytics and artificial intelligence capabilities. As a Databricks Data Engineer, you will support the design, build, and optimization of cloud-based data engineering solutions that enable large-scale transformation. You will work with business and technology teams to modernize data environments, support analytics and artificial intelligence use cases, and deliver measurable business outcomes. This role offers the opportunity to help clients implement enterprise-scale Databricks solutions that improve platform performance and expand data-driven decision-making., As a Databricks Data Engineer on the Core AI & Data team, you will be responsible for:

• Design, build, and maintain data pipelines and data engineering solutions using Databricks, Apache Spark, Python, and Structured Query Language (SQL)
• Support the modernization of enterprise data platforms by implementing cloud-based ingestion, transformation, and storage patterns
• Develop and maintain batch and streaming data workflows that support reporting, analytics, and artificial intelligence use cases
• Apply data architecture, integration, and data modeling practices to improve data quality, scalability, and platform performance
• Collaborate with client and Deloitte teams to troubleshoot issues, implement enhancements, and support delivery of large-scale data transformation programs

• 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, * Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or Statistics

• 3+ years of experience in data engineering, extract, transform, load (ETL) development, or data platform engineering
• 2+ years of experience building data pipelines in Databricks using Apache Spark, Python, and Structured Query Language (SQL)
• Experience implementing data models, data integration patterns, and cloud-based data processing workflows
• Experience working with at least one cloud platform: Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP)
• Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
• Limited immigration sponsorship may be available.

Preferred:

• Experience with Delta Lake, Databricks Workflows, and Unity Catalog
• Experience using Git-based version control and continuous integration/continuous deployment pipelines
• Experience supporting batch and streaming data workloads
• Experience with data warehousing, lakehouse architecture, and performance optimization
• Experience supporting analytics or machine learning data pipelines
• Experience working in consulting or client service delivery environments

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 $86,700 to $170,900.

Deloitte’s Core AI & Data practice helps organizations modernize data platforms, strengthen enterprise data foundations, and scale analytics and artificial intelligence capabilities across the business. The team works with clients to architect, engineer, and deploy cloud-based data solutions that improve decision-making, enable innovation, and support large-scale transformation. Practitioners collaborate across business and technology functions to solve complex challenges in data modernization, governance, platform engineering, and insight delivery.