Data Platform Lead – Databricks & AI Solutions

Markel Corporation; Omaha (NE); On-site; USD 109,000 - 227,000; Full time

Benefits offered by this job

Health insurance

401(k) with employer match

Employee Stock Purchase Plan

Paid time off

Corporate holidays & floating holidays

Parental leave

Job summary

Markel Corporation is seeking a data engineering leader to manage a team delivering a scalable data platform on Databricks. You will drive strategic goals, supervise performance reviews, and mentor staff while coordinating with stakeholders across the organization.

The role emphasizes architectural design, delivery discipline, and ongoing process improvements. Qualifications include 8–10 years in data engineering, strong leadership, and experience with medallion architecture, AI/ML integration,

Qualifications

• Hands-on Databricks experience and data platform delivery.
• Experience with medallion architecture (Raw, Refined, Presentation).
• Strong leadership and mentoring across multiple teams.
• Experience with AI/ML in data engineering contexts.
• Knowledge of ETL tools and best practices.

Responsibilities

• Leads a team of data engineers and aligns delivery with business goals.
• Plans performance appraisals, recruitment, and staff development.
• Manages multiple teams, balancing workload and priorities.
• Designs, builds, and delivers data platform components on Databricks.
• Tracks metrics and reports status to senior management.

Skills

Databricks

Data engineering

Agile methodologies

Medallion architecture

AI/ML in data

ETL best practices

Team leadership

Coaching & mentoring

Stakeholder communication

Education

Bachelor's degree in CS/IS/related field

Tools

Databricks

ETL tools

Job description

Markel Corporation is seeking a data engineering leader to manage a team delivering a scalable data platform on Databricks. You will drive strategic goals, supervise performance reviews, and mentor staff while coordinating with stakeholders across the organization.

The role emphasizes architectural design, delivery discipline, and ongoing process improvements. Qualifications include 8–10 years in data engineering, strong leadership, and experience with medallion architecture, AI/ML integration,