Staff Data Engineer

Company Overview Ghost is an AI-native inventory distribution platform and operating system for modern retail trade. We partner with the world’s best brands to help them understand the true value of their inventory and route it to the right destinations globally. Ghost gives brands precise control over where and how their inventory is sold. Backed by top venture firms including L Catterton, Cathay Innovation, Union Square Ventures, Equal Ventures, and Eniac. Ghost has offices in Los Angeles and New York. About the Role We are looking for a Staff Data Engineer to join our team and play a pivotal role in delivering high-quality data solutions. Our data landscape has grown organically and needs consolidation, standardization, and strategic redesign. You’ll be leading a comprehensive overhaul of our data infrastructure, working on critical business reporting, complex data integration, data warehousing, and data modeling projects. You are a creative, problem solver who works directly with stakeholders to leverage your expertise in reporting, data warehousing, ETL/ELT development, cloud-based data platforms, and technical solutioning. You will aggregate our data from different sources to create dashboards that will support business strategy and growth. Key Responsibilities: Audit existing data infrastructure and create a roadmap for consolidation and modernization Pair with business stakeholders to derive reporting requirements Design and implement data integration strategies and develop efficient data pipelines to synchronize dispersed data sources Work with large and complex datasets, including structuring, cleaning, and transforming data Develop and optimize ETL/ELT processes to transform, clean, and structure large and complex datasets Collaborate with cross-functional product teams to understand business requirements and develop data-driven solutions Lead the design and implementation of scalable data models to support analytics and reporting needs Drive the adoption of best practices in data engineering, data governance, and data quality to ensure the integrity and reliability of our data Manage projects and initiatives, applying Agile methodologies to ensure timely and successful delivery of data engineering solutions Architect and build data warehousing solutions to ensure efficient storage and retrieval of data Stay updated with the latest trends and advancements in data engineering technologies, tools, and techniques, and assess their potential for enhancing our data infrastructure and capabilities Qualifications: Bachelor's or Master's degree in computer science, engineering, or a related field. Experience with being an early data engineer within a fast-moving and dynamic startup environment 7+ years of experience in data engineering, including hands-on experience with data warehousing, ETL/ELT development, and cloud-based data platforms. Solid expertise in SQL (e.g., PostgreSQL), relational databases, and NoSQL databases. Experience with cloud platforms (AWS) and their data services (e.g., Snowflake, Redshift). Proven track record of delivering high-quality data solutions, with a focus on scalability and performance. Excellent project management skills with experience in Agile methodologies. Strong problem-solving abilities and attention to detail. Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams and stakeholders This role is based in Los Angeles. Our total compensation for this position can range from $180,000 - $220,000. The actual amounts may vary based on factors such as experience, knowledge, skills, and abilities related to the position. This position is contract to hire. Benefits we offer: Medical, Vision, and Dental with some plans covered at 100% Competitive compensation and equity structure 401K Unlimited PTO Ghost is an equal opportunity employer and values diversity in the workplace. We are committed to fostering an inclusive and innovative environment where all employees can thrive. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other protected characteristic under applicable laws.