Sr Databricks Data Engineer

Deloitte is seeking a Senior Databricks Data Engineer to join the AI and Data practice in Tempe, Arizona on site. This role focuses on designing, building, and optimizing cloud based data engineering solutions to modernize data platforms, enable analytics and AI use cases, and drive data driven decision making across large scale enterprise transformations. The position offers a salary range of USD 116,200 to 229,100 per year and requires a bachelor’s degree in Computer Science, Engineering, or a related field with a minimum of one year of experience.

Responsibilities

• Champion Best Practices: Define, document, and promote leading approaches for data architecture, integration, and modeling.
• Pipeline Ownership: Design, develop, and maintain robust data pipelines and architectures that support enterprise data needs at scale.
• Drive Excellence: Lead initiatives to enhance data quality, operational efficiency, and process scalability.
• Team and Technology Lead: Assess, pilot, and integrate new big data and analytics technologies; mentor data engineers and architects to ensure effective project delivery.
• Data Governance: Advise on and implement governance, security, and compliance strategies for modern cloud data ecosystems.
• Communication: Translate technical concepts and business value for executives, business leads, and technology teams.
• DevOps and Automation: Oversee CI/CD practices with tools such as Azure DevOps, AWS Code Pipeline, Jenkins, TFS, or PowerShell to streamline deployments and operations.

Requirements

• Ability to work independently and collaboratively within a team.
• Strong written and verbal communication skills.
• Meticulous attention to detail and quality of work.
• Ability to build and maintain professional relationships.
• Capacity to lead projects or workstreams.
• Ability to manage 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 data engineering experience focusing on Databricks on AWS, Azure, or GCP.
• Experience with Lakehouse architecture, Apache Spark, Delta Lake, cloud native databases, storage solutions, and distributed compute platforms.
• Experience with data warehousing, 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 Delta Live Tables, Autoloader, Structured Streaming, Databricks Workflows, Apache Airflow, Unity Catalog, automated CI/CD pipelines, and optimization of data pipelines, code, and compute resources.
• Willingness to travel up to 50 percent depending on assignment and client needs.
• Limited immigration sponsorship may be available.

Qualifications Required

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 5+ years of hands on data engineering experience with a focus on Databricks on AWS, Azure, or GCP.
• Experience with Lakehouse architecture, Apache Spark, Delta Lake, cloud native databases, storage solutions, and distributed compute platforms.
• Experience with data warehousing, 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, with experience in Delta Live Tables, Autoloader, Structured Streaming, Databricks Workflows, Apache Airflow, Unity Catalog, automated CI/CD pipelines, and performance optimization of data pipelines and compute resources.
• Ability to travel 50 percent on average based on project requirements.
• Limited immigration sponsorship may be available.

Preferred

• Master’s degree in Computer Science, Engineering, or a related field.
• Experience across one or more cloud ecosystems (AWS, Azure, GCP) and associated big data services.
• Proficiency in tuning and optimizing performance within Databricks and Apache Spark environments.
• Experience with Databricks Lakeflow.
• Background in artificial intelligence and machine learning solutions.

Technologies

• Databricks, Delta Lake, Delta Live Tables, Autoloader, Structured Streaming, Databricks Workflows, Unity Catalog, Databricks Lakeflow
• Apache Spark, PySpark
• AWS, Azure, GCP
• Azure DevOps, AWS Code Pipeline, Jenkins, TFS, PowerShell
• Lakehouse architectures, cloud-native databases, and distributed compute platforms
• Apache Airflow

The Team

Deloitte's Core AI and Data practice assists organizations in modernizing data platforms, strengthening enterprise data foundations, and scaling analytics and AI capabilities across the business. The team collaborates with clients to architect, engineer, and deploy cloud-based data solutions that improve decision making, drive innovation, and support large-scale transformation. Practitioners work across business and technology functions to solve complex data modernization challenges.