Senior Engineering Manager, Data

Responsibilities

Lead and grow the team

• Coach engineers through clear expectations, feedback, and career development.
• Hire and retain top talent and build a high-performance, inclusive culture.
• Establish delivery and operational rituals, including planning, retrospectives, and incident reviews.

Own the data platform strategy

• Define and evolve architecture for ingestion, transformation, orchestration, governance, and data products.
• Drive a roadmap balancing foundational platform investments with product delivery needs.
• Champion best practices, including dbt patterns, data contracts, testing, and documentation.

Deliver high-quality systems

• Ensure pipelines and models are accurate, observable, secure, and scalable.
• Improve reliability through alerting, SLAs and SLOs, runbooks, and root-cause analysis.
• Partner with platform engineering on deployment patterns, cost optimization, and environment strategy.

Partner cross-functionally

• Collaborate with Product, Analytics, Security, and Engineering leaders to enable customer and business outcomes.
• Communicate tradeoffs, risks, and timelines clearly with stakeholders.
• Influence the broader organization on data quality, trust, and accountability.

Be a hands-on player-coach

• Stay close to the work through architecture reviews, pairing, design documents, and occasional implementation.
• Provide judgment on tooling and build-versus-buy decisions across Snowflake, dbt, and Sigma.

Requirements

• 5+ years of experience in an engineering management role leading teams in a fast-paced, high-growth environment.
• Direct experience leading a data engineering or data platform team.
• Proven ability to scale teams and systems through hiring, process, architecture, and delivery.
• Excellent communication and collaboration skills across technical and non-technical stakeholders.
• Player-coach mindset with prior individual contributor experience.
• Hands-on familiarity with Snowflake, dbt, or Sigma, with deep experience in at least one.
• Experience building modern data platforms, including ELT, modeling layers, governance, and self-serve analytics.
• Travel approximately five to six times per year, including company-wide Connect Weeks and additional leadership travel to Nashville, TN or another designated location.

Preferred Qualifications

• Experience with streaming data patterns and event-driven architectures using Kafka.
• Experience operating production systems in AWS and partnering with platform and SRE teams.
• Exposure to AI/ML or data science workflows.
• Comfort working in TypeScript and Python ecosystems for data-adjacent services and tooling.
• Familiarity with data quality testing, lineage, observability, and access control patterns.

Compensation and Benefits

• Annual salary range: $225,000–$265,000 USD.
• Equity in the form of stock options.
• Medical, dental, and vision coverage.
• Unlimited PTO.
• Learning Grant program for professional development.
• 401(k) with match and expedited vesting for US employees.