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Sr Data Engineer at Stord. Location Information: Remote - All US, United States. . Stord is The Consumer Experience Company, powering seamless checkout through delivery for today's leading brands. Combining comprehensive commerce-enablement technology with high-volume fulfillment services provides brands a platform to compete with retail giants. Stord manages over $10 billion of commerce annually through its fulfillment, warehousing, transportation, and operator-built software suite including OMS, Pre- and Post-Purchase, and WMS platforms. Stord is leveling the playing field for all brands to deliver the best consumer experience at scale.. With Stord, brands can increase cart conversion, improve unit economics, and drive customer loyalty. Stord’s end-to-end commerce solutions combine best-in-class omnichannel fulfillment and shipping with leading technology to ensure fast shipping, reliable delivery promises, easy access to more channels, and improved margins on every order.. Hundreds of leading DTC and B2B companies like AG1, True Classic, Native, Seed Health, quip, goodr, Sundays for Dogs, and more trust Stord to deliver industry-leading consumer experiences on every order. Stord is headquartered in Atlanta with facilities across the United States, Canada, and Europe. Stord is backed by top-tier investors including Kleiner Perkins, Franklin Templeton, Founders Fund, Strike Capital, Baillie Gifford, and Salesforce Ventures.. Stord is seeking a highly experienced Senior Data Engineer to join our innovative team and play a critical role in shaping our data landscape. You will be instrumental in leading initiatives to enhance our data . pipelines. , optimize our data warehouse, and empower the business through robust data solutions. This position offers a unique chance to apply your expertise with modern data tools within a rapidly developing environment, collaborating with a diverse group of data analysts, product managers, and engineering teams to deliver solutions that drive platform improvements and significant business value.. What You'll Do. As a Senior Data Engineer, you'll be at the forefront of our data strategy, focusing on:. Data Architecture & Development. Design and implement scalable, reliable data pipelines using modern data engineering tools and technologies.. Lead the re-architecture of our data warehouse to significantly enhance performance, scalability, and data quality.. Develop and maintain robust data models, ensuring data accuracy, consistency, and integrity through effective cleansing, transformation, and validation processes.. Collaborate closely with engineers, analysts, and stakeholders to deeply understand data requirements and translate them into efficient data solutions.. Data Infrastructure Management. Build and maintain our data infrastructure on Google Cloud Platform (GCP), including data lakes, data warehouses, and data pipelines, optimizing for both performance and cost efficiency.. Proactively monitor data pipeline performance, identify bottlenecks, and troubleshoot issues to ensure seamless data flow.. Implement and enforce data security and governance best practices to protect sensitive information and maintain compliance.. Machine Learning Enablement. Prepare and transform high-quality data for machine learning models, ensuring consistency and reliability for optimal model performance.. Facilitate seamless data access for machine learning algorithms and tools, empowering our AI team.. Support the AI team with basic data analysis and reporting tasks and collaborate with engineering to integrate ML solutions into the Stord platform.. Collaboration & Leadership. Provide technical guidance and mentorship to junior members of the data team, fostering a culture of continuous learning and growth.. Champion data democratization across the organization, promoting a data-driven decision-making culture.. Document data pipelines and data models comprehensively for knowledge sharing and long-term maintainability.. Communicate effectively with cross-functional teams and stakeholders, translating complex technical concepts into clear, actionable insights.. What You'll Need. 5+ years of hands-on experience in data engineering or a closely related field, with a proven track record of building and maintaining complex data pipelines and data warehouses.. Expert-level proficiency in SQL and Python.. Extensive experience with cloud platforms, preferably GCP, including building and managing data infrastructure.. Strong expertise with data pipeline orchestration tools such as Apache Airflow, Prefect, or similar.. Demonstrated experience with modern data warehousing technologies like BigQuery or Snowflake.. Familiarity with data lake concepts and technologies.. Proficiency with data transformation tools (e.g., dbt).. Solid understanding of data engineering best practices and experience with version control systems (e.g., Git).. Exceptional problem-solving and analytical skills with a keen eye for detail.. Excellent English communication and collaboration skills, with the ability to thrive independently and as part of a dynamic team.. Bonus Points. A foundational understanding of machine learning concepts, data preparation techniques, and model evaluation.. Experience in the logistics or supply chain industry.. Prior experience working in a fast-paced startup environment.. .