Sr Databricks Data Engineer
Apache Airflow
Automation
Azure
Azure Databricks
Big Data
Bigdata
Cloud
Cloud Operations
Cloud Platforms
Data
Data Analysis
Data Analytics
Data Architecture
Data Engineer
Data Governance
Data Integration
Data Lake
Data Lakehouse
Data Pipeline
Data Platform
Data Processing
Data Security
Data Warehouse
Database
Databricks
Databricks Workflows
Delta Lake
Delta Live Tables
DevOps
Engineer
Engineering
ETL
Google Cloud
Information Technology (IT)
Integration
Spark
SQL
Technical Lead
Job Description
Sr Databricks Data Engineer role with Deloitte in Seattle, WA (onsite), offering USD 137,500 - 193,600 per yearly and travel up to 50%.
Responsibilities
- Define and codify best practice standards for data architecture, integration, and data modeling, and promote their adoption across projects.
- Take ownership of designing, building, and sustaining robust data pipelines and architectures that serve enterprise-scale data needs.
- Lead initiatives to boost data quality, streamline operations, and scale data processing processes.
- Assess, pilot, and adopt emerging big data and analytics technologies to keep the organization at the forefront.
- Mentor and develop data engineering and architecture teams to support technical growth and successful project delivery.
- Advise on, design, and implement governance, security, and compliance frameworks for modern cloud data ecosystems.
- Translate complex technical concepts and business value to executives, business leaders, and technology stakeholders.
- Oversee CI/CD adoption and automation using tools like Azure DevOps, AWS Code Pipeline, Jenkins, TFS, and PowerShell to streamline deployments and operations.
- Provide clear guidance to team members and stakeholders.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related field
- 5+ years of hands-on data engineering experience with Databricks on AWS, Azure, or GCP
- Experience with Lakehouse architectures, Apache Spark, Delta Lake, cloud-native databases and 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
- Ability to travel 50% on average based on client work
- Limited immigration sponsorship may be available
- Master's degree in Computer Science, Engineering, or a related field
- Experience in one or more of AWS, Azure, and GCP cloud ecosystems and their 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
Technologies
- Databricks
- Delta Lake
- Delta Live Tables
- Autoloader
- Structured Streaming
- Databricks Workflows
- Unity Catalog
- Apache Airflow
- Azure DevOps
- AWS Code Pipeline
- Jenkins
- TFS
- PowerShell
- PySpark
- Apache Spark
- Databricks Lakeflow
- AWS
- Azure
- GCP
Benefits
- Discretionary annual incentive program
- Core Talent Model benefits package
- Reasonable accommodations for people with disabilities
The Team
Deloitte's Core AI and Data practice assists clients in modernizing data platforms, strengthening enterprise data foundations, and scaling analytics and AI capabilities across the organization. The team designs, engineers, and deploys cloud-based data solutions that support informed decision making, drive innovation, and enable large-scale transformation. Practitioners collaborate across business and technology functions to tackle data modernization challenges.
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