Senior Data Engineer

Accountabilities: In this role, you will own the reliability, scalability, and evolution of the organization’s data infrastructure while partnering with teams across the business to deliver trusted insights and solutions. You will contribute to improving data maturity, enabling analytics and AI-driven initiatives, and ensuring data systems are built with long-term sustainability in mind. Own the reliability, availability, accuracy, and performance of core data infrastructure while maintaining strong data privacy and governance standards. Design, build, and optimize end-to-end data pipelines using modern data engineering practices and technologies. Develop centralized, reusable data models and semantic layers that support business intelligence, analytics, and AI/ML workflows. Create and maintain reliable data integrations, including Reverse ETL pipelines, APIs, and data feeds supporting business and growth initiatives. Partner with Analysts, Product Managers, Engineers, Marketing, Legal, Fraud, and other stakeholders to translate business requirements into effective data solutions. Establish data quality standards, monitoring practices, SLAs, and observability frameworks to proactively identify and resolve issues. Improve data governance practices by defining standards, closing operational gaps, and promoting responsible data usage. Introduce new data sources, enhance existing models, and continuously improve the organization’s data capabilities. Support marketing and customer engagement initiatives through accurate and scalable data feeds across external platforms. Advocate for strong engineering practices by building intuitive, maintainable systems and sharing knowledge with teammates and stakeholders. Requirements: The ideal candidate is an experienced data engineer who combines strong technical expertise with business understanding, ownership, and excellent collaboration skills. You should be comfortable operating independently, solving complex problems, and building systems that serve both technical and non-technical users. 5+ years of experience in software engineering, data engineering, or related technical roles. Strong experience designing, building, and maintaining complete data pipelines from ingestion through consumption. Advanced SQL skills and strong proficiency in Python. Hands-on experience with modern data stack technologies such as Snowflake, dbt, Airflow, Fivetran, Segment, Looker, Amplitude, Algolia, AWS/Lambda, and Git. Experience designing, consuming, and maintaining APIs and data integrations. Strong understanding of analytics engineering principles and scalable data architecture. Experience implementing data quality monitoring, alerting, and governance practices. Ability to manage projects from discovery and planning through execution and delivery. Strong communication skills with the ability to collaborate effectively with engineers, executives, and business stakeholders. Comfortable working autonomously in a fast-paced environment with changing priorities. Pragmatic approach to technology decisions, focusing on solving business challenges rather than adopting tools for their own sake. Nice to have: Experience supporting machine learning workflows, search and discovery systems, retail technology, resale platforms, or marketplace businesses. Benefits: Competitive salary range based on location and experience: Tier 1 locations: $128,000 - $160,000 USD Tier 2 locations: $115,200 - $144,000 USD Tier 3 locations: $108,800 - $136,000 USD Overall compensation range: $108,800 - $160,000 USD. Medical, dental, and vision insurance coverage. 401(k) retirement plan. Paid time off and company holidays. Disability and life insurance options. Remote work flexibility across the United States. Opportunity to work on large-scale data systems powering a global digital marketplace. Collaborative environment with opportunities to influence technical direction and business outcomes.