Deloitte's Core AI & Data team is seeking a Databricks Data Engineer to design, build, and optimize cloud-based data pipelines that power AI-enabled analytics. This onsite role in Atlanta, GA centers on modernizing data platforms with Databricks, Apache Spark, Python, and SQL, while collaborating with business and technology colleagues to achieve meaningful, measurable outcomes.
Location
Atlanta, GA (onsite)
Compensation
USD 86,700 - 170,900 per year
Responsibilities
- Design, build, and maintain data pipelines and engineering solutions on Databricks using Apache Spark, Python, and SQL
- Support the modernization of enterprise data platforms by implementing cloud-based ingestion, transformation, and storage patterns
- Develop and manage batch and streaming data workflows that underpin reporting, analytics, and AI use cases
- Apply data architecture, integration, and modeling practices to improve data quality, scalability, and platform performance
- Collaborate with client and Deloitte teams to troubleshoot issues, implement enhancements, and support large-scale data transformation programs
Requirements
- Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or Statistics
- 3+ years of experience in data engineering, ETL development, or data platform engineering
- 2+ years of experience building data pipelines in Databricks using Apache Spark, Python, and SQL
- Experience implementing data models, data integration patterns, and cloud-based data processing workflows
- Experience working with at least one cloud platform: AWS, Microsoft Azure, or Google Cloud Platform (GCP)
- Ability to travel ~50% on average, depending on engagements
- Limited immigration sponsorship may be available
Technologies
- Databricks
- Apache Spark
- Python
- SQL
- Delta Lake
- Unity Catalog
- Databricks Workflows
- Git and Git-based version control
- AWS
- Microsoft Azure
- Google Cloud Platform (GCP)
- CI/CD
The team
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. Practitioners architect, engineer, and deploy cloud-based data solutions that improve decision-making, enable innovation, and support large-scale transformation, collaborating across business and technology functions to tackle data modernization challenges.
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
Accommodation
Information for applicants with a need for accommodation: Accommodation information
