Senior Data Engineer

About the role

Welcome to the Data Engineering team at GOAT Group, where you will play a critical role in strengthening the data infrastructure that powers a leading online marketplace for fashion resale. In this position, you will own the design, reliability, and performance of core data systems that touch nearly every department within the organization. You will be responsible for ensuring that data is dependable, accessible, and accurate while adhering to the highest standards of privacy and compliance. The ideal candidate is passionate about building robust, scalable systems and thrives in a collaborative environment with a focused and dedicated team. You will partner closely with analysts, product managers, engineers, and marketers to turn business questions into actionable data insights. This role offers the opportunity to work on impactful projects that directly influence user experience and business outcomes across the company. If you are driven by data quality and enjoy solving complex infrastructure challenges, this is a chance to make a meaningful contribution to a growing business.

Key facts

What you'll do

• Ensure the dependability, accessibility, and accuracy of our data systems, adhering to privacy regulations.
• Develop, manage, and refine data pipelines using Snowflake, DBT, Airflow, and Looker.
• Construct reusable data models for business-wide use, designed for AI and machine learning applications.
• Establish a standardized layer for metric and dimension definitions to bring clarity and consistency to analytics.
• Work with Analysts, Product Managers, Engineers, and Marketing teams to translate business needs into technical data solutions.
• Create and maintain Reverse ETL pipelines in Python, and build or utilize APIs for seamless data movement between systems.
• Integrate new data sources, optimize existing models, and define service level agreements for critical data products.
• Promote data governance and improve organizational data maturity through the implementation of standards and responsible data handling practices.
• Manage data feeds for marketing initiatives, customer retention efforts, and growth marketing platforms such as Google Shopping and Meta.
• Support the end-to-end data lifecycle by designing ingestion processes, ensuring data quality, and enabling consumption across the organization.
• Collaborate with stakeholders to document requirements, validate outcomes, and ensure that data solutions align with business goals.
• Mentor and guide junior team members by sharing best practices, conducting code reviews, and fostering a culture of continuous improvement.

Requirements

• A minimum of 5 years of professional experience in engineering, with a strong background in software and data engineering, and familiarity with analytics engineering.
• Hands-on experience with Snowflake, DBT, Airflow, Fivetran, Segment, Looker, Amplitude, Algolia, AWS Lambda, and Git.
• Extensive experience in building, maintaining, and architecting complete data pipelines from data ingestion through to consumption and analysis.
• Proficiency in SQL for writing complex queries, optimizing performance, and ensuring data integrity.
• Strong programming skills in Python, with the ability to write clean, maintainable code for data processing and automation.
• Demonstrated experience building and interacting with APIs to enable data exchange between applications and services.
• A proven track record of delivering reliable data solutions in a production environment while adhering to compliance and privacy standards.
• Excellent problem-solving skills and the ability to diagnose issues, troubleshoot pipeline failures, and implement effective resolutions.
• Strong communication skills, with the ability to translate technical concepts into clear insights for both technical and non-technical audiences.

Nice to have

• Familiarity with machine learning workflows and an understanding of how data engineering supports model development and deployment.
• Exposure to search and discovery technologies, including tools like Algolia and similar platforms.
• Previous experience working in retail, resale, or marketplace environments, with an understanding of unique domain challenges.

Skills & tools

• Snowflake
• DBT
• Airflow
• Fivetran
• Segment
• Looker
• Amplitude
• Algolia
• AWS Lambda
• Git
• Python
• SQL
• APIs

Practical notes

Compensation ranges from $108,800 to $160,000 USD annually, varying by US location tier. Benefits include a 401K plan, paid time off, and options for dental, medical, vision, disability, and life insurance. Please include a brief note of one to three lines at the bottom of your resume explaining your interest in Grailed and this role. Additionally, share a recent experience related to buying or selling on a peer-to-peer marketplace that stood out to you.

Hours, travel, visa, and application deadlines are not specified in the source material.