What we offer
Join Deloitte's Core AI & Data practice in Tempe, AZ on-site, with a salary range of USD 116,200 to 229,100 per year. A Bachelor's degree in Computer Science, Engineering, or a related field is required. You will help design, build, and optimize cloud-based data engineering solutions that modernize data platforms, enable analytics and AI use cases, and drive data-driven decision-making across large-scale enterprise transformations.
As part of the Core AI & Data team, you will collaborate across business and technology functions to solve complex data modernization challenges, support data-driven innovation, and contribute to ongoing leadership in data engineering practices. This role provides opportunities to lead, mentor, and shape how data initiatives are delivered in a fast-paced enterprise environment.
Responsibilities
- Champion Best Practices: Establish, document, and promote best-in-class approaches for data architecture, integration, and modelling.
- Pipeline Ownership: Oversee the design, development, and maintenance of robust data pipelines and data architectures that support large-scale, enterprise data needs.
- Drive Excellence: Initiate and manage efforts to improve data quality, operational efficiency, and process scalability.
- Team and Technology Lead: Evaluate, pilot, and integrate new big data and analytics technologies, ensuring the organization remains at the cutting edge. Lead, coach, and develop teams of data engineers and architects, fostering technical growth and effective project delivery.
- Data Governance: Consult on, design, and implement governance, security, and compliance strategies tailored to modern cloud data ecosystems.
- Communication: Communicate technical concepts and business value to diverse stakeholders, including executives, business leads, and technology teams.
- DevOps and Automation: Oversee the implementation of CI/CD practices with tools such as Azure DevOps, AWS Code Pipeline, Jenkins, TFS, or PowerShell for streamlined deployments and operations.
Requirements
- 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
- Bachelor's degree in Computer Science, Engineering, or a related field
- 5+ years of hands-on experience in data engineering with a focus on Databricks on AWS, Microsoft Azure, or Google Cloud Platform
- Experience with Lakehouse architecture, Apache Spark, Delta Lake, cloud-native databases, storage solutions, and distributed compute platforms
- Experience with data warehousing, third normal form (3NF), dimensional modeling, enterprise data lakes, incremental data loads, and metadata-driven ingestion and data quality frameworks using PySpark
- 1+ year leading complex, cross-functional data projects and technical teams, including experience with Delta Live Tables, Autoloader, Structured Streaming, Databricks Workflows, Apache Airflow, Unity Catalog, automated CI/CD pipelines, and performance optimization of data engineering pipelines, code, and compute resources
- 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
Technologies
- Databricks
- Azure DevOps
- AWS Code Pipeline
- Jenkins
- TFS
- PowerShell
- Delta Lake
- Apache Spark
- PySpark
- Delta Live Tables
- Autoloader
- Structured Streaming
- Databricks Workflows
- Apache Airflow
- Unity Catalog
- Databricks Lakeflow
- AWS
- Azure
- GCP
About 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. The team architects, engineers, 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.
Preferred qualifications
- Master's degree in Computer Science, Engineering, or a related field
- Experience in one or more of AWS, Azure, and GCP cloud ecosystems and associated big data services
- Experience tuning and optimizing performance in Databricks and Apache Spark environments
- Experience with Databricks Lakeflow
- Experience with artificial intelligence and machine learning solutions
