Note: The job is a remote job and is open to candidates in USA. Commerce is hiring a Data Engineering Manager to lead its Enterprise Data Engineering team and own the roadmap for its Snowflake- and Airflow-based data platform. The role combines hands-on technical leadership, team development, and adoption of AI-assisted and agentic workflows for building, testing, and monitoring data pipelines and products.
Responsibilities
- 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
Skills
- 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
- 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
Benefits
- Remote role
- May be eligible for variable compensation (such as bonus or commission), in accordance with local policies
- May be eligible for equity, in accordance with local policies
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