Lead Data Engineer

World Market•Alameda, CA

41d•Remote

About The Position

World Market is seeking a Lead Data Engineer to design and implement scalable data pipelines and data infrastructure. This role involves creating trusted data models for analytics, building reusable frameworks, and owning the end-to-end delivery and support of data products. The position requires strong communication skills and the ability to thrive in a virtual work environment, with a preference for candidates located on or near the West Coast. This is a fully remote position.

Requirements

10+ years of data engineering experience maintaining data platform technologies and supporting analytical teams.
5+ years of hands-on experience with cloud data warehouse platforms (Snowflake).
Expert knowledge of SQL and Python.
Hands-on experience with pipeline orchestration tools (Airflow) and data transformation tooling (dbt).
Working knowledge of Git, CI/CD practices (GitHub Actions/Jenkins), and Infrastructure as Code (Terraform).
Hands-on experience with Kimball data warehouse modeling methodologies, alongside strong data modeling, data quality, and documentation practices.
Experience in API design.
Experience providing production support, monitoring pipeline health, and triaging platform alerts to guarantee data delivery SLAs.
Experience performing root cause analysis for production issues and identifying opportunities for data platform improvement.
Passionate about writing clean, documented, and well-formed code, and performing regular code reviews.
Experience setting technical standards, mentoring engineers, and balancing platform scalability with domain-specific delivery needs.
Track record of partnering with business stakeholders in customer, product, or merchandising domains to translate requirements into robust data models.
Ability to work cross-functionally with Enterprise Architect, Security, and Cloud Infra teams, as well as collaborating with offshore teams.
Excellent written and verbal communication skills, with a proven ability to break down complex technical topics for non-technical audiences.

Nice To Haves

Retail experience preferred.
Real-time streaming experience is a plus.

Responsibilities

Design and implement scalable data pipelines and data infrastructure that support various business domains (customer, product, merchandising, and other data domains).
Design and implement data transformations, cleaning, and validation logic to produce trusted, well-documented data models for analytics use cases.
Build reusable frameworks, templates, and self-service tooling so both engineering and business teams can move faster.
Own source code management, documentation (technical and end-user), and release planning for data engineering products; lean into DataOps, DevOps, and CI/CD to deliver reliable, tested, and scalable functionality through automation.
Own end-to-end delivery and day-to-day production support of data products, actively monitoring pipeline health and troubleshooting failures to guarantee uptime and meet data delivery SLAs.
Document data definitions, transformations, and lineage for datasets you own.
Partner with the Snowflake Admin/Architect to evaluate new platform capabilities, design patterns, and storage/compute optimizations that accelerate delivery timelines.
Evaluate and adopt new tools and technologies to improve platform capability and speed of analytics delivery.
Partner with Analytics, Security, and Cloud Infra teams to ensure best practices are defined and implemented.
Partner directly with business stakeholders to translate business questions into data models and self-service datasets.
Set standards and patterns for how domain-specific data products are built on the platform; mentor engineers working across platform and analytics.