Manager, Data Engineering

BigCommerce • Austin, TX

4d • Remote

About The Position

Commerce is seeking an AI-first Data Engineering Manager to lead its Enterprise Data Engineering team. The manager will own the roadmap and architecture for the enterprise data platform, built primarily on Snowflake and orchestrated with Apache Airflow, supporting reporting, analytics, AI, and data products across the business. This is a hands-on leadership role for someone with production data-pipeline experience, prior team leadership, and a practical interest in agentic workflows.

The role combines team leadership with technical contribution. The manager will mentor engineers in data engineering practices and the use of coding agents, and will help build and govern autonomous pipeline and data-quality agents. Agentic workflows should include clear guardrails, evaluation, and human-in-the-loop review. The manager will partner across Analytics, Data Science, Product, and business teams to deliver reliable, well-governed data products, while improving platform quality, observability, lineage, cost efficiency, and reliability.

Requirements

• 7+ years of experience in data engineering.
• 3+ years of direct experience managing or leading a team of data engineers.
• Deep, hands-on production experience with Snowflake and Apache Airflow, including performance tuning, cost management, and workflow orchestration at scale.
• Experience working with distributed teams across time zones.
• Strong SQL and Python skills, with the ability to review or write pipeline code alongside the team.
• Experience with dbt, Fivetran, Airbyte, or similar modern ELT tooling alongside Snowflake and Airflow.
• Professional engineering workflow experience using AI coding assistants or agentic tools such as Claude Code, GitHub Copilot, Cursor, or Snowflake CoCo.
• A track record of mentoring and developing engineers, including engineers who are more senior or specialized in a particular area.
• Working knowledge of data modeling, data governance, and data security and compliance practices.
• Excellent communication skills and the ability to translate technical tradeoffs into business terms and vice versa.
• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Nice To Haves

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

Responsibilities

• Lead, mentor, and grow a team of data engineers, including hiring, onboarding, career development, and performance management.
• Own the technical roadmap and architecture for Commerce’s Enterprise Data platform, primarily built on Snowflake and orchestrated with Airflow.
• Embed agentic tools, such as Claude Code, into daily workflows for pipeline development, testing, documentation, and code review.
• Coach and upskill engineers in agentic data engineering, including agent-assisted or autonomous data-quality checks, self-healing pipelines, and LLM-powered data products, with appropriate 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 and Airflow platform.
• Modernize data pipelines and evaluate new data and AI tooling.
• Establish scalable design review, incident response, and documentation practices.
• Report on team health, delivery, and platform reliability to engineering and business leadership.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager