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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** STORD, Inc. - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Data Analysis, BigQuery, Data Cleansing, Information Engineering, Data Infrastructure, Data Transformation, Data Security, Data Warehousing, Document-Oriented Databases, Python (Programming Language), Machine Learning, Software Tools, DataOps, SQL Databases, Data Storage Management, Google Cloud, Snowflake, Model Validation, Git, Data Lakes, Software Version Control, Data Pipelines - **Published:** June 9, 2026 - **Apply:** https://www.dice.com/job-detail/6015cc45-bb0c-4678-83b8-6e5b06e52d72 ## About the Role * 5+ years of experience in data engineering or a related field. * Proven experience building and maintaining data pipelines and data warehouses. * Experience with cloud platforms, preferably Google Cloud Platform. * Experience with SQL and data modeling. * Experience with data transformation tools such as dbt, or similar. Technical Skills: * Strong proficiency in SQL and Python. * Experience with data pipeline tools (e.g., Apache Airflow, Prefect, or similar). * Experience with data warehousing technologies (e.g., BigQuery, Snowflake). * Familiarity with data lake concepts and technologies. * Understanding of data engineering best practices. * Understanding of basic machine learning concepts, data preparation techniques, and model evaluation. * Experience with version control systems (e.g., Git). Soft Skills: * Strong problem-solving and analytical skills. * Excellent communication and collaboration skills. * Ability to work independently and as part of a team. * Strong attention to detail. Bonus Points: * Basic understanding of data science concepts, including common machine learning models and statistical analysis. * Experience with machine learning data preparation. * Experience in the logistics or supply chain industry. * Experience in a startup environment. ## Description * Design, develop, and maintain scalable and reliable data pipelines using modern data engineering tools and technologies. * Help drive the re-architecture of our data warehouse to improve performance, scalability, and data quality. * Implement data cleansing, transformation, and validation processes to ensure data accuracy and consistency. * Collaborate with other engineers and stakeholders to define data requirements and develop data models. Data Infrastructure Management: * Build and maintain data infrastructure on Google Cloud Platform, including data lakes, data warehouses, and data pipelines. * Optimize data storage and retrieval for performance and cost efficiency. * Monitor data pipeline performance and troubleshoot issues. * Implement data security and governance best practices. Machine Learning Support: * Prepare and transform data for machine learning models, ensuring data quality and consistency. * Enable data access for machine learning algorithms and tools. * Assist with basic data analysis and reporting tasks to support the AI team. * Work with the engineering team to support ML models. Collaboration and Communication: * Work closely with engineers, data scientists, and product managers to understand data needs and deliver solutions. * Document data pipelines and data models for knowledge sharing and maintainability. * Communicate effectively with team members and stakeholders. Team Guidance and Collaboration: * Provide technical guidance and mentorship to the data team. * Foster a culture of innovation and collaboration within the data team. * Collaborate with cross-functional teams to integrate ML solutions into the Stord platform. * Drive data democratization and promote data-driven decision-making. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Got AI ideas but no money? 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