Lead, mentor, and grow a team of analysts at multiple career levels, building skills in SQL, dbt, data modeling, and stakeholder communication.
Conduct regular 1:1s, design reviews, and PR reviews, providing timely and actionable technical feedback that accelerates analyst growth.
Own the full hiring lifecycle for analytics roles, from defining job requirements through offer, and build onboarding programs that accelerate ramp time.
Foster a culture of engineering excellence, experimentation, documentation, and continuous improvement.
Make decisions as a team: the systems you build will be maintained and extended by others, so defensible design decisions and high collaboration are non-negotiable.
Define and drive the technical roadmap for data transformations and the analytics layer, establishing dbt modeling and quality patterns and standards that scale across the organization.
Evaluate and champion emerging technologies and best practices in data analytics, including responsible adoption of AI tooling
Establish data governance frameworks, quality standards, and lineage documentation practices that support audit and compliance requirements in a regulated insurance environment
Participate in on-call rotation for data availability as part of a shared rotation with Data Engineering; this is lightweight and shared across the team.
Lead the analytics team's evolution from legacy nightly batch delivery processes to real-time, API-driven data infrastructure to ensure the analytics transformation layer, schemas, and partner-facing data products mature to support real-time consumption patterns alongside existing batch workflows.
Develop and execute the migration roadmap to move partner data delivery from batch-oriented pipelines to API-driven architectures, managing the complexity of running dual delivery patterns during the transition while maintaining data quality and partner SLAs.
Partner with Product and Engineering to support enterprise partner integrations, ensuring the analytics layer delivers consistent, quality-assured data whether consumed via legacy batch processes or emerging real-time APIs.
Drive cross-functional initiatives that require coordination across data, product, engineering, and business teams
Represent the data team in architecture forums, planning sessions, and stakeholder reviews
Communicate complex technical concepts clearly to non-technical executives, building alignment and driving informed decision-making
Build strong relationships with external partners and vendors where analytics deliverables support enterprise integrations.

Requirements

10+ years in data analytics, analytics engineering, or a closely related data role, with at least 3 years in a people management capacity leading teams of 5 or more direct reports
Expert SQL and data modeling proficiency (particularly with large columnar databases such as BigQuery, Snowflake, Redshift).
Expert dbt skills building and maintaining transformation layers, enforcing testing and documentation standards, and establishing dbt best practices across a team
Demonstrated ability to coach and grow analysts at multiple career levels, from early-career analysts learning the craft to senior analysts developing toward technical leadership
Experience contributing to or leading data governance initiatives, including data quality frameworks, access controls, lineage documentation, and standards that support audit or compliance requirements
Working knowledge of designing analytics layers that serve both batch and real-time consumption patterns, via streaming or event-driven data architectures, and the ability to collaborate effectively with data engineering teams that own pipeline infrastructure
Proven track record of working with Product and Engineering to deliver data products, not just reports, including defining data contracts, shaping analytics requirements, and contributing to platform decisions
Strong written and verbal communication skills, with the ability to distill complex data concepts for non-technical executive audiences and drive alignment across competing stakeholder priorities
Demonstrated experience with AI Coding assistants – AI tools are heavily ingrained in Bestow culture.
Proven track record designing an end-to-end data pipeline in cloud frameworks (such as GCP, AWS, Azure) with requirements from multiple stakeholders
Experience with creating alerts and monitoring pipelines that contribute to overall data governance.

Benefits

Competitive salary and equity based on role
Policies and managers that support work/life balance, like our flexible paid time off and parental leave programs
100% paid-premium option for medical, dental, and vision insurance
Lifestyle stipend to support your physical, emotional, and financial wellbeing
Flexible work-from-home policy and open to remote
Remote and WFH options, as well as a beautiful, state-of-the-art office in Dallas’ Deep Ellum, for those who prefer an office setting
Employee-led diversity, equity, and inclusion initiatives

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLdata modelingdbtdata governancedata quality frameworksreal-time data architecturesAPI-driven architecturesdata pipeline designcloud frameworksanalytics engineering

Soft Skills

mentoringcoachingcommunicationcollaborationleadershiprelationship buildingdecision-makingcross-functional coordinationtechnical feedbackcontinuous improvement