Commerce — the company behind BigCommerce, Feedonomics, and Makeswift is looking for an AI-first Data Engineering Manager to lead our Enterprise Data Engineering team. You'll own the roadmap for the Snowflake- and Airflow-based platforms that power reporting, analytics, AI and data products across the business, while building a team that treats AI agents as first-class teammates in the data engineering lifecycle.

This is a hands-on leadership role for someone who has shipped production data pipelines, has led engineers before, and is genuinely energized by agentic workflows — not as a buzzword, but as a daily practice for how data gets built, tested, and monitored. You'll spend real time coaching your team on best practices in data engineering: pairing with coding agents, building and governing autonomous pipeline and quality agents, and raising the team's bar for speed and craft.

What you’ll do

• Lead, mentor, and grow a team of data engineers — hiring, onboarding, career development, and performance management
• Own the technical roadmap and architecture for Commerce’s Enterprise Data platform, built primarily on Snowflake and orchestrated with Airflow
• Champion an AI-first way of working by embedding agentic tools (e.g., Claude Code) into the team’s daily workflow for pipeline development, testing, documentation, and code review
• Coach and upskill engineers on agentic data engineering — designing agent-assisted or autonomous data quality checks, self-healing pipelines, and LLM-powered data products — with clear guardrails, evaluation, and human-in-the-loop review
• Partner with Analytics, Data Science, Product, and business stakeholders to translate data needs into reliable, well-governed data products
• Set and enforce standards for data quality, observability, lineage, and cost efficiency across the Snowflake/Airflow estate
• Drive modernization of data pipelines and evaluate new data and AI tooling to keep the platform on the cutting edge
• Establish design review, incident response, and documentation practices that scale the team’s impact without scaling headcount 1:1.
• Report on team health, delivery, and platform reliability to engineering and business leadership

Who you are

• 7+ years in data engineering, with 3+ years directly managing or leading a team of data engineers.
• Deep, hands-on experience with Snowflake and Apache Airflow in production, including performance tuning, cost management, and workflow orchestration at scale.
• Experience working with distributed teams across time zones.
• Strong SQL and Python skills, and comfort reviewing or writing pipeline code alongside your team.
• Experience with dbt, Fivetran/Airbyte, or similar modern ELT tooling alongside Snowflake and Airflow.
• Real experience using AI coding assistants or agentic tools (e.g., Claude Code, GitHub Copilot, Cursor), Snowflake CoCo in a professional engineering workflow
• A track record of mentoring and developing engineers, including those more senior or specialized than you in a given area.
• Working knowledge of data modeling, data governance, and data security/compliance practices.
• Excellent communication skills — you can translate technical tradeoffs into business terms and back again.
• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Nice to have

• Experience designing or operating agentic workflows: LLM-driven pipeline monitoring, autonomous anomaly detection, RAG-based data catalogs/search, or agent frameworks such as LangGraph, AutoGen, or MCP-based tooling.
• Background in ecommerce, SaaS, or marketplace data (order, catalog, or customer data at scale).
• Experience building internal platforms or self-service tooling that let analysts and other engineers move faster.
• Familiarity with cost governance and FinOps practices for cloud data platforms.

Work Where You Thrive:

For candidates based in the Austin or Atlanta metro area, the position follows a hybrid work model with three days per week in the office, balancing focused individual work with meaningful in-person collaboration.

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Pay Transparency: $150,000 - $220,000

The national base salary range for this role is posted above in this job post.

Final compensation will be determined based on factors such as relevant experience, skills, qualifications and geographic location. We also consider internal equity to help ensure fair and consistent pay practices across our teams.

Where applicable, this role may also be eligible for variable compensation (such as bonus or commission), equity, and benefits in accordance with local policies. Details will be shared during the hiring process. We are committed to equitable and transparent pay practices that align to market data, internal equity, and individual contribution.