Manager, Data Engineering

Qdoba•San Diego, CA

30d

About The Position

Qdoba is seeking a visionary Manager of Data Engineering to architect the next-generation, AI-driven data ecosystem. This leader will design and scale cloud-native platforms that power real-time insights and predictive analytics. The ideal candidate combines deep expertise in Microsoft SQL Server technologies (SSIS, SSRS, SSAS, Power BI) with advanced proficiency in modern cloud solutions like Snowflake and integration tools such as Matillion. You will lead a global team of data engineers, driving cloud migrations, building streaming pipelines, and enabling intelligent automation across the enterprise. Beyond technical mastery, you'll champion innovation-leveraging AI, machine learning, and cutting-edge data architectures to transform how Qdoba harnesses information to drive business value.

Requirements

Bachelor's or Master's degree in Computer Science, Information Systems, or related field.
8+ years of experience in data engineering or BI development.
3+ years of experience in a leadership or managerial role.
Strong hands-on experience with SQL Server, SSIS, SSRS, SSAS, and Power BI.
Strong understanding of data warehousing concepts and dimensional modeling.
Experience with performance tuning and optimization of SQL queries and ETL processes.
Excellent communication, leadership, and project management skills.
Ability to work in a fast-paced, collaborative environment.
Familiarity with LLMs like Claude, Copilot, and ChatGPT.
Demonstrated experience staying current with industry trends and emerging technologies in AI, data engineering and analytics.

Nice To Haves

Familiarity or willingness to learn Snowflake, Matillion, and other cloud-based data technologies.
Experience with cloud platforms (e.g., Snowflake, Databricks, or comparable).
Familiarity with data governance and compliance frameworks.
Knowledge of Python, R, or other scripting languages for data manipulation.
Experience with Agile methodologies and CI/CD pipelines for data solutions.

Responsibilities

Lead and mentor a team of data engineers in designing, developing, and maintaining scalable data pipelines and solutions.
Architect and implement ETL processes using SQL Server Integration Services (SSIS).
Develop and maintain reports and dashboards using SQL Server Reporting Services (SSRS) and Power BI.
Design and manage multidimensional and tabular models using SQL Server Analysis Services (SSAS).
Drive migration and adoption of modern data platforms like Snowflake and ETL tools such as Matillion.
Ensure data quality, integrity, and security across all data platforms.
Optimize database performance and troubleshoot complex data issues.
Drive best practices in data engineering, including version control, testing, and documentation.
Manage project timelines, resources, and deliverables.
Collaborate with business stakeholders to gather requirements and translate them into technical solutions.