Data Engineer

About The Company

Stord is a leading technology-driven logistics company dedicated to transforming the consumer experience through seamless delivery solutions. Headquartered in Atlanta, with operational facilities across the United States, Canada, and Europe, Stord leverages innovative commerce-enablement technology combined with high-volume fulfillment services to empower brands to compete effectively in the retail landscape. Backed by top-tier investors such as Kleiner Perkins, Franklin Templeton, Founders Fund, Strike Capital, Baillie Gifford, and Salesforce Ventures, Stord is experiencing rapid growth, with plans to double revenue within the next 18 months. The company's platform manages over $10 billion in commerce annually, providing comprehensive solutions that include fulfillment, warehousing, transportation, and proprietary software suites like OMS, WMS, and pre/post-purchase tools. Stord’s mission is to level the playing field for brands, delivering exceptional consumer experiences at scale and enabling them to increase conversion rates, improve unit economics, and foster sustained customer loyalty.

About The Role

We are seeking an experienced and innovative Senior Data Engineer to join our dynamic team at Stord. In this pivotal role, you will be instrumental in enhancing our data infrastructure, optimizing data pipelines, and transforming data into a strategic asset that drives business growth. You will be responsible for designing, developing, and maintaining scalable data solutions that support our analytics, machine learning, and operational needs. Collaborating closely with data analysts, data scientists, product managers, and engineering teams, you will help shape the future of data-driven decision-making at Stord. This position offers a unique opportunity to work with cutting-edge tools and technologies in a fast-paced environment, contributing directly to the company's strategic objectives and technological advancement.

Qualifications

The ideal candidate will possess a strong background in data engineering, with at least five years of relevant experience. Proficiency in cloud-based data platforms, particularly Google Cloud Platform (GCP), is essential. Candidates should have extensive experience building and maintaining data pipelines and data warehouses, with a solid understanding of SQL, data modeling, and data transformation tools such as dbt. Technical expertise in Python, data pipeline orchestration tools like Apache Airflow or Prefect, and data warehousing solutions such as BigQuery or Snowflake is required. A good understanding of data lake concepts, data security, governance, and best practices in data engineering is also necessary. Familiarity with machine learning concepts, data preparation, and basic statistical analysis will be considered a plus. Strong problem-solving, communication, and collaboration skills are essential for success in this role.

Responsibilities

• Design, develop, and maintain scalable, reliable, and efficient data pipelines using modern data engineering tools and technologies.
• Lead efforts to re-architect and optimize the data warehouse infrastructure, improving performance, scalability, and data quality.
• Implement data cleansing, transformation, validation, and enrichment processes to ensure high data accuracy and consistency across platforms.
• Collaborate with cross-functional teams to gather data requirements, define data models, and develop comprehensive data solutions.
• Build and manage data infrastructure on GCP, including data lakes, warehouses, and pipelines, ensuring optimal performance and cost efficiency.
• Monitor data pipeline performance, troubleshoot issues, and implement improvements proactively.
• Establish and enforce data security, privacy, and governance standards in line with industry best practices.
• Prepare and transform data for machine learning models, ensuring quality and accessibility for AI initiatives.
• Support data analysis, reporting, and visualization tasks to facilitate data-driven decision-making.
• Work closely with data scientists and ML engineers to enable model development and deployment through reliable data pipelines.
• Document data processes, pipelines, and models thoroughly to promote knowledge sharing and maintainability.
• Provide technical mentorship and guidance to junior team members, fostering a culture of continuous learning and innovation.
• Drive initiatives to democratize data access and promote a data-centric culture within the organization.

Benefits

Stord offers a comprehensive benefits package designed to support the well-being and professional growth of our employees. This includes competitive salary packages, health, dental, and vision insurance, and a 401(k) retirement plan with company matching. We promote work-life balance through flexible working hours and remote work options. Employees have access to ongoing training and development opportunities, fostering continuous learning and career advancement. Additionally, Stord encourages a collaborative and inclusive work environment, recognizing and rewarding innovation and excellence. Our culture emphasizes transparency, teamwork, and a shared commitment to transforming the logistics industry through technology and data-driven solutions.

Equal Opportunity

Stord is an equal opportunity employer committed to fostering an inclusive environment for all employees. We celebrate diversity and are dedicated to creating a workplace that respects and values individual differences. All employment decisions are made based on qualifications, merit, and business needs, without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, age, disability, or any other protected characteristic. We believe that diverse teams drive innovation and are essential to our success and growth.