Sr Databricks Data Engineer

Senior Databricks Data Engineer based in Sacramento, CA, on site, focusing on designing, building, and optimizing cloud data solutions to modernize platforms and enable analytics and AI at enterprise scale.

Responsibilities

• Establish and promote best practices for data architecture, integration, and modeling across projects.
• Own the design, development, and maintenance of robust data pipelines and architectures supporting large-scale enterprise data needs.
• Lead initiatives to improve data quality, operational efficiency, and scalable processes.
• Evaluate, pilot, and integrate new big data and analytics technologies; lead and develop teams of data engineers and architects.
• Consult on and implement governance, security, and compliance strategies for modern cloud data ecosystems.
• Translate technical concepts and business value for executives, business leads, and technology teams.
• Oversee CI/CD practices and automation with tools such as Azure DevOps, AWS Code Pipeline, Jenkins, TFS, or PowerShell.
• Provide clear guidance to colleagues across project teams.

Requirements

• Ability to work independently and collaboratively within a team.
• Effective written and verbal communication skills.
• Meticulous attention to detail and quality of work product.
• Ability to build and sustain professional relationships.
• Proven ability to lead projects or workstreams.
• Strong capability to manage and prioritize multiple tasks in a fast-paced, dynamic environment.
• Strong interpersonal skills and professional demeanor.
• Ability to meet deadlines.

Technologies

• Databricks
• AWS
• Azure
• GCP
• Delta Lake
• Apache Spark
• PySpark
• Unity Catalog
• Delta Live Tables
• Autoloader
• Structured Streaming
• Databricks Workflows
• Apache Airflow
• Azure DevOps
• AWS Code Pipeline
• Jenkins
• TFS
• PowerShell
• Databricks Lakeflow

Qualifications Required

• 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 performance optimization of data engineering pipelines, code, and compute resources
• Ability to travel 50% on average, depending on client engagements
• 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 related 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