> Markdown version of [/jobs/ext/4690687-data-engineer-i](https://www.wearedevelopers.com/jobs/ext/4690687-data-engineer-i). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer I - **Company:** Harvest, Inc. - **Location:** United States - **Experience:** Starter - **Contract:** Permanent contract - **Skills:** Sql Data Warehouse, Airflow, BigQuery, Code Review, Information Systems, Data Architecture, Dimensional Modeling, Performance Tuning, Scrum Methodology, Cloud Services, Standard Sql, DataOps, Server Administration, Software Engineering, SQL Databases, Data Processing, Scripting, Snowflake, Git, Kubernetes, Information Technology, Data Lineage, Data Management, Software Version Control, Data Pipelines - **Published:** November 12, 2026 - **Apply:** https://www.careerbuilder.com/job-details/data-engineer-i--503fdc0b-7442-4237-8666-b19673868212 ## About the Role Retail, Consumer Branding, Intellectual Property (IP), Performance Tuning/Optimization, Performance Analysis, Storytelling, Analysis Skills, Software Development, Software Administration, Data Management, Working SQL skills, including joins, aggregations, CTEs, and window functions. - Familiarity with version control (Git) and collaborative development workflows. - Curiosity, attention to detail, and demonstrated follow-through. - Excellent written and verbal communication skills in English. - Ability to collaborate effectively with U.S.-based teams and clients across time zones. - Ownership mindset with a proactive approach to problem solving and continuous improvement. Nice to Have: - Bachelor's degree in Computer Science, Data Science, Information Systems, or equivalent experience. - Exposure to a SQL-based transformation framework (dbt preferred). - Exposure to a cloud data warehouse (Snowflake, BigQuery, or Redshift). - Familiarity with an orchestration platform (Airflow, Astro, or Prefect). - Basic Python scripting for data processing and automation. - Understanding of data modeling patterns (dimensional modeling, normalization). - Exposure to CPG or retail data (Kroger / 84.51, Walmart / Luminate, Nielsen, Circana). We encourage all interested candidates to apply. Please note that we only accept resumes submitted in English. ## Description Data reporting and insights: standardized and optimized reports and performance trackers for U.S. teams and clients - Analytical storytelling: leveraging data to tell a compelling story - Software development: supporting the dynamic needs of our team - Tool creation: building easy-to-use solutions to complex data problems - Data operations and cloud data management: building and maintaining data pipelines from source - systems to cloud data storage, and retrieving data from a wide variety of sources, The Data Engineer I contributes to the development, testing, and maintenance of data pipelines that power Harvest Group's data products across retail partners including Walmart, Sam's Club, Target, Amazon, Costco, and Kroger. This is an entry-level engineering role focused on building foundational skills in SQL, transformation frameworks, and cloud data platforms. The Data Engineer I works alongside senior engineers to deliver reliable, well-tested data transformations and models. This role combines the core competencies of data architecture and data operations into a unified engineering discipline., Develop and test transformation models and SQL following team conventions and coding standards. - Support the build-out of new data pipelines for retailer data products alongside senior engineers. - Investigate and resolve data quality issues escalated from product support. - Write and maintain data tests, schema documentation, and source freshness checks. - Monitor scheduled pipeline runs and troubleshoot basic failures. - Participate in Agile/Scrum delivery, including sprint planning, daily standups, and retrospectives. - Participate in code reviews, learning from feedback and improving over time. - Document resolutions, processes, and data lineage in the team knowledge base. - Grow your understanding of the retail data landscape and how Harvest Group technology supports clients across multiple retailers.