Data Pipeline Engineer

Location/Onsite: Lehi / Salt Lake City, UT | Hybrid (1–2 days per week in office) Our client is seeking a Data Pipeline Engineer to join their growing technology team in the Lehi/Salt Lake City area. This hybrid role is perfect for someone who loves building reliable data infrastructure, solving complex data challenges, and creating scalable systems that power business intelligence and AI initiatives. Do you enjoy building data pipelines that people can trust? Are you passionate about creating clean, reliable data for analytics and AI? Do you thrive in fast-paced environments where you can take ownership and make a measurable impact? If so, this could be the perfect Data Pipeline Engineer opportunity for you. Keep reading to learn more! The Perks! Compensation: $125,000–$155,000 base salary, depending on experience Benefits: Full benefits package Special Perks: Hybrid schedule with just 1–2 in-office days per week, opportunity to build the data foundation behind AI-powered business operations, high-impact role with significant ownership and autonomy A Day in the Life of the Data Pipeline Engineer As the Data Pipeline Engineer, you'll own the infrastructure that powers our client's internal data ecosystem. You'll build and maintain reliable pipelines, improve data quality, and ensure critical business systems—including reporting, executive dashboards, and AI-powered tools—always have accurate, trustworthy information. Your work will directly support smarter business decisions and help scale a rapidly growing Amazon-focused organization. Responsibilities include: Own and maintain the company's Snowflake data warehouse Design, build, and optimize production data pipelines Develop and maintain Amazon Seller Central, Vendor Central, and SP-API integrations Transform and model data using dbt Schedule, monitor, and manage workflows using Airflow or Astronomer Maintain and troubleshoot Fivetran connectors and ETL/ELT processes Build Google Workspace data ingestion pipelines for Drive, Gmail, and Google Sheets Create monitoring, alerting, and automated data quality checks Improve data freshness, reliability, lineage, and observability Build trusted data models for reporting, operational dashboards, and AI systems Collaborate with business stakeholders to validate data accuracy Document data architecture, pipeline ownership, and source-of-truth standards Support AI agents with reliable structured and unstructured data sources Identify and resolve pipeline failures before they impact business operations Requirements and Qualifications: 2+ years of experience maintaining production data pipelines Experience working with Amazon marketplace data, including Seller Central, Vendor Central, or Amazon SP-API Experience building pipelines for Amazon operational data such as inventory, advertising, sales, catalog, account health, or reporting Strong experience with Snowflake Hands‑on experience with dbt Experience with Airflow and/or Astronomer Experience supporting Fivetran or similar ETL/ELT platforms Python experience for automation, APIs, or data workflows Experience with Google Workspace APIs (Drive, Gmail, Sheets, OAuth, service accounts, or domain‑wide delegation) Strong understanding of data quality concepts including freshness, reconciliation, deduplication, schema management, and lineage Comfortable owning production systems that directly impact business decisions Strong communication skills with both technical and non‑technical stakeholders Utah resident able to work onsite in the Lehi/Salt Lake City area 1–2 days per week Experience supporting AI agents, LLM workflows, RAG systems, or observability tooling is a plus Experience in e-commerce, Amazon operations, agency environments, or multi‑client data ecosystems is preferred About the Hiring Company: Our client is an established Amazon agency that partners with more than 40 consumer brands to optimize their marketplace performance. As they continue investing in automation and AI-driven operations, they're building a world-class data platform that powers reporting, operational insights, and intelligent decision‑making. This is an opportunity to make a lasting impact on the company's technology foundation while working alongside a collaborative, forward‑thinking team. If you're excited about building dependable data infrastructure, solving complex engineering challenges, and helping power next‑generation AI systems, we'd love to hear from you. #J-18808-Ljbffr