Data Engineer

Company Description Outdoor Holding Company (NASDAQ: POWW) owns and operates , the largest and most trusted online marketplace for firearms, ammunition, and hunting and shooting sports accessories in the United States. The technology-driven platform connects millions of buyers and sellers through a secure, compliant, and scalable digital ecosystem tailored to regulated products and enthusiast-focused commerce. The marketplace supports a diverse network of federally licensed dealers, retailers, manufacturers, and individual sellers, backed by robust compliance tools and integrated payment solutions. The company is investing heavily in technology, data capabilities, user experience, and AI to enhance intelligent search, personalization, fraud detection, compliance, and pricing insights. Outdoor Holding Company follows a disciplined, growth-oriented strategy that strengthens marketplace network effects and delivers long-term value to its stakeholders.Role is seeking a Data Engineer (Marketplace Data, Search & AI) to help transform marketplace data into better experiences for buyers and sellers. This role will build and maintain the data foundation that powers search, recommendations, structured product data, pricing insights, and other customer-facing features.The ideal candidate will bring deep expertise in either search and discovery or data engineering/database architecture, along with a working knowledge of the other area. You will partner closely with software engineers, product teams, and QA to build scalable data solutions, optimize search performance, and ensure data is accessible, trusted, and actionable across the organization.This is an AI-native role where you'll leverage AI tools and agents to improve development efficiency, enhance search relevance, and support data-driven decision-making while maintaining strong standards for validation, governance, and compliance.Required Qualifications5+ years of hands-on experience in data engineering, database engineering, or search engineering within high-traffic production environments.Strong SQL expertise and experience building data pipelines that synchronize data across transactional, analytical, and search systems. Daily experience using AI tools and agents to improve productivity while validating outputs for accuracy and quality.Experience with source control and database migration tools such as Git, SSDT, Flyway, or Liquibase. Deep expertise in at least one of the following:Search and discovery technologies such as Elasticsearch, OpenSearch, or Solr, including search quality measurement, relevance tuning, and A/B testing. Relational database engineering, preferably SQL Server, including performance tuning, indexing strategies, execution plans, and scalable data architecture. Working knowledge of both search systems and data engineering concepts.Preferred QualificationsExperience in both search engineering and advanced data engineering. Advanced Elasticsearch expertise, including mappings, analyzers, aliases, and cluster reindexing. Strong SQL Server and T-SQL experience, including optimization and refactoring of complex stored procedures. Hands-on DBA experience with backup/recovery, high availability, security, and capacity planning. Experience with semantic search, vector search, embeddings, hybrid ranking, or AI-assisted search relevance. Experience supporting e-commerce or marketplace search at scale. Background in recommendation engines, personalization, event tracking, and A/B testing. Experience with structured product data, taxonomy management, or catalog optimization. Experience working with cloud data platforms, NoSQL/document databases, messaging systems, or event streaming technologies. Python or similar programming experience for data automation and engineering. Experience in regulated or compliance-focused industries. Location: Remote (Preference for Atlanta Metro Area) | Visa Sponsorship: Not Available