Data Engineering Supervisor

Texas Farm Bureau and Affiliated Companies•Waco, TX

9d•Onsite

About The Position

The Data Engineering Supervisor is responsible for leading and developing a team of Data Engineers and Pipeline Engineers to deliver high-quality, scalable, and reliable data solutions. This role combines technical leadership, people management, and delivery accountability, ensuring that data engineering work is executed efficiently, consistently, and aligned with business priorities. This position plays a critical role in establishing strong engineering discipline, reducing delivery friction, and driving team autonomy, while partnering closely with Architecture, Product, QA, and Business teams.

Requirements

Bachelor’s degree in Computer Science, Data Management, Information Systems, or related field.
Proven experience in a leadership or supervisory role preferred.
Strong experience with data engineering and enterprise data management environments.
Experience coordinating work across analysts, developers, and technical teams.
Strong communication and stakeholder management skills.
Advanced SQL development and query optimization capability.
Experience designing and implementing ETL/ELT data pipelines across complex data environments.
Strong familiarity with data modeling concepts including dimensional modeling (star schema) and data warehousing design.
Hands-on experience with cloud data platforms (Azure Data Factory, Azure Synapse/Fabric, Azure Data Lake, Azure SQL).
Ability to design and manage end-to-end data pipelines across layered architectures (Bronze, Silver, Gold).
Experience with data orchestration and workflow management tools (ADF pipelines, Databricks).
Proficiency in Python and/or scripting languages used for data processing and automation.
Experience with integrating data from multiple source systems (e.g., transactional systems, APIs, legacy databases such as DB2).
Strong understanding of data quality, validation, and reconciliation processes for ensuring data accuracy and reliability.
Experience with monitoring, alerting, and troubleshooting production data pipelines.
Experience implementing security controls such as Row-Level Security (RLS) and data access management.
Understanding of performance tuning techniques for queries, pipelines, and cloud data workloads.
Experience with version control (Git) and CI/CD practices for deploying data pipelines and data platform changes.
Experience with BI and reporting platforms (Power BI preferred) and understanding of downstream data consumption.
Demonstrated ability to manage and mentor cross-functional team members.
Excellent verbal, written, and presentation skills.
Ability to synthesize technical concepts into business-aligned actions.
Skilled in issue triage, root cause analysis, and prioritization under pressure.

Nice To Haves

Microsoft Azure Data Engineer Associate (DP-203 or Fabric equivalents)
Databricks Data Engineer Certification
Data Product Ownership experience
Experience working in regulated industries (e.g., insurance, finance, or healthcare).
Familiarity with agile or hybrid project methodologies.
Valid Texas driver’s license and driving record at the time of hire which would not place the employee on probation or disqualify the employee from Certified Fleet Operator status under the Company Driving and Safety Policy.

Responsibilities

Supervise, coach, and mentor Data Engineers and Pipeline Engineers.
Set clear expectations for ownership, accountability, and delivery standards.
Conduct performance reviews, provide ongoing feedback, and support career development.
Support hiring, onboarding, and training of new team members.
Work alongside Project Managers to plan and manage team capacity across multiple initiatives.
Assign work to ensure balanced workloads and efficient delivery across both project and production workstreams.
Track delivery progress and proactively manage risks and dependencies.
Establish and enforce data engineering standards and best practices.
Ensure consistent code review, documentation, and testing discipline.
Promote reusable components and scalable design patterns.
Provide oversight of data pipelines, integrations, and transformations.
Ensure reliability, performance, monitoring, and operational readiness.
Partner with Architecture to align implementations with enterprise platforms.
Coordinate delivery with offshore engineering partners.
Ensure consistent quality, communication, and delivery standards.
Ensure consistent use of JIRA for work intake, tracking, and reporting.
Monitor progress, remove blockers, and improve delivery predictability.
Translate business priorities into actionable engineering work.