Sr Data Engineer

Sonata Software • San Antonio, TX

2d • 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 involves designing, building, and maintaining scalable data pipelines and workflows in Snowflake, using dbt for modular transformations and Fivetran for automated ingestion. The Senior Data Engineer will architect and optimize the enterprise data warehouse, apply data modeling and performance-tuning practices, and support data quality, security, compliance, cataloging, lineage, and stewardship in partnership with governance teams.

The position works closely with business and analytics teams to translate requirements into scalable data solutions and uses AWS services, primarily S3, for reliable, performant, and cost-effective data storage and integration. The role is based in Irvine, California, with three days per week working from the office. The position 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.
• Strong collaboration and communication skills, including working with cross-functional teams and translating 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.
• Experience with visualization platforms such as Power BI, Tableau, or Looker to support self-service analytics.
• Ability to mentor junior engineers and contribute to engineering best practices.
• Familiarity with broader AWS data services beyond S3.

Responsibilities

• Design, build, and maintain scalable data pipelines and workflows in Snowflake, using dbt for modular transformations and Fivetran for automated ingestion.
• Architect and optimize the enterprise data warehouse, applying data modeling, performance-tuning, and scalability best practices.
• 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 reliable, performant, and cost-effective data storage and integration.
• Manage and troubleshoot data ingestion pipelines and connectors.
• Contribute to engineering best practices and mentor junior engineers, as described among the preferred qualifications.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior