Sr Data Engineer

Flexstaf IT • Irvine, CA

12h • Hybrid

About The Position

The Senior Data Engineer will be part of a team designing and implementing a modern data platform to support enterprise-wide analytics, integration, and AI/ML initiatives. The team will build a scalable enterprise data warehouse, enable modern visualization tools, and advance self-service analytics capabilities for business users.

The role designs, builds, and maintains scalable data pipelines and workflows in Snowflake, using dbt for modular transformations and Fivetran for automated ingestion. It also architects and optimizes the enterprise data warehouse, applies data modeling and performance-tuning best practices, and supports data governance, quality, security, and compliance. The Senior Data Engineer works with business and analytics teams to translate requirements into scalable solutions and uses AWS services, primarily S3, for reliable, performant, and cost-effective data storage and integration.

The position is based in Irvine, California, with three days per week working from the office. The role is listed as CTH.

Requirements

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
• At least 5 years of professional experience in data engineering or related roles.
• Proven expertise with Snowflake for data pipelines, development, and optimization.
• Strong experience with dbt for modular transformations and Fivetran for automated ingestion.
• Solid background in data warehousing, dimensional modeling, and performance tuning.
• Hands-on experience with AWS cloud services, especially S3, for data integration and storage.
• Familiarity with data governance tools such as Alation or Atlan for cataloging, lineage, and stewardship.
• Proficiency in SQL and comfort with scripting languages such as Python.
• Expert-level Snowflake and SQL skills; advanced dbt, Fivetran, data warehousing, and data modeling skills; intermediate AWS, data governance, and Python skills.
• Ability to collaborate and communicate with cross-functional teams and translate technical concepts to business stakeholders.
• Awareness of how AI/ML can support data engineering practices and willingness to experiment and learn.

Nice To Haves

• Master's degree in a related field.
• Experience with real-time or streaming technologies such as Kafka, Kinesis, or Flink.
• Knowledge of data security, compliance, and access-control best practices.
• Exposure to AI/ML workflows and integrating data engineering solutions with ML pipelines.
• Background with visualization platforms such as Power BI, Tableau, or Looker to support self-service analytics.
• Demonstrated ability to mentor junior engineers and contribute to engineering best practices.
• Familiarity with broader AWS data services.

Responsibilities

• Design, build, and maintain scalable data pipelines and workflows in Snowflake, leveraging dbt for modular transformations and Fivetran for automated ingestion.
• Architect and optimize the enterprise data warehouse using best practices in data modeling, performance tuning, and scalability.
• Partner with governance teams to document data cataloging, lineage, and stewardship, and ensure data quality, security, and compliance.
• Work with business and analytics teams to translate requirements into scalable data solutions.
• Use AWS services, primarily S3, for data storage and integration while ensuring reliability, performance, and cost-effectiveness.

What This Job Offers

• Career Level: Senior