Senior Data Engineer

As eHub continues to grow, a trusted data infrastructure is becoming increasingly critical to how we scale operations, support decision-making, and power future AI initiatives. We are looking for a Senior Data Engineer to help modernize and operationalize eHub’s analytics platform, ensuring reliable, scalable, and well-governed data across the organization.

This is an opportunity to play a foundational role within a fast-growing logistics technology company where data engineering directly impacts operational visibility, financial reporting, product analytics, customer experience, and AI-enabled innovation. The ideal candidate is excited to build systems, introduce engineering rigor, and create a reliable data foundation that enables the business to scale confidently., The Senior Data Engineer (Analytics Platform) plays a critical role in building and scaling eHub’s modern analytics infrastructure. This role partners closely with Product, Engineering, Finance, Revenue Operations, Analytics, and eHub’s Chief AI Officer to deliver reliable data pipelines, trusted business metrics, and scalable analytics workflows that support operational and strategic decision-making across the company.

This is a highly hands-on role for someone who enjoys solving complex data engineering challenges while building operationally mature systems. The ideal candidate combines strong technical execution with a pragmatic, business-oriented mindset and is passionate about improving data reliability, observability, and scalability.

In addition to building and maintaining data pipelines and warehouse architecture, this role will help establish engineering best practices across the analytics stack, including automated testing, monitoring, governance, documentation, and CI/CD workflows. This individual will also mentor junior analysts and help elevate overall data maturity and trust in analytics across the organization., Data Platform & Warehouse

• Own the architecture and operational health of eHub’s analytics platform (currently AWS Redshift)
• Design scalable ELT workflows and dimensional data models for analytics and AI use cases
• Evaluate and implement improvements across orchestration, transformation, observability, and governance tooling
• Manage warehouse performance, cost optimization, access controls, and retention policies

Pipeline Engineering & Reliability

• Build and maintain reliable ingestion pipelines from operational systems including NetSuite, HubSpot, and eHub’s application databases
• Implement automated data quality checks, anomaly detection, lineage tracking, and alerting
• Introduce software engineering best practices into the analytics stack, including:
• CI/CD for data pipelines
• automated testing
• version-controlled transformations
• deployment workflows
• monitoring and incident response
• Reduce operational risk by replacing manual or custom-scripted workflows with maintainable platform standards

Analytics Engineering & Enablement

• Partner with analysts and business stakeholders to deliver clean, trusted, well-documented datasets
• Define semantic models, business definitions, and reusable transformation patterns
• Support self-service analytics and BI initiatives within Domo and downstream tools

Cross-Functional Collaboration

• Partner closely with Engineering on schema evolution, source system integrations, and platform architecture
• Collaborate with Product, Finance, RevOps, and Data Science teams to prioritize high-impact data initiatives

Do you have experience in Schema design?, Required

• 5+ years building and operating production-grade cloud data platforms
• Strong SQL skills and hands-on experience with modern ELT architectures
• Experience with AWS analytics tooling (Redshift, S3, Glue, Lambda, Airflow/MWAA, or similar)
• Experience implementing data quality, observability, and monitoring practices
• Familiarity with dimensional modeling and analytics engineering concepts
• Experience supporting BI/reporting environments with reliable curated datasets
• Strong communication skills and ability to work cross-functionally with technical and business teams
• Full-time on-site in Sandy, Utah office.

Strongly Preferred

• Experience with dbt for transformation, testing, and analytics engineering workflows
• Experience with data observability and quality tooling (Monte Carlo, Soda, Great Expectations, Deequ, etc.)
• Experience implementing CI/CD workflows for analytics engineering and data pipelines
• Familiarity with SaaS integrations (NetSuite, HubSpot, Salesforce, Stripe, etc.)
• Experience working in startup or lean-team environments
• Experience supporting Domo or similar modern BI platforms (Looker, Tableau, Power BI, Sigma, etc.)
• Familiarity with dashboard reliability, semantic consistency, and downstream analytics dependencies

Pulled from the full job description

• Professional development assistance
• Tuition reimbursement
• Parental leave
• 401(k)
• Health insurance
• Paid time off
• Vision insurance, * Join a dynamic and innovative team passionate about transforming the logistics and fulfillment industry.
• Work on technology and products that directly impact merchants, fulfillment providers, and customer experiences.
• Help shape product strategy, operational improvements, and data-driven innovation across the company.
• Collaborate closely with leadership, product teams, and AI initiatives in a fast-moving growth environment.
• Help grow and shape eHub’s analytics capabilities and culture.
• Competitive salary and benefits package, including health insurance, retirement plans, and paid time off.
• Opportunity for career growth and leadership within a rapidly growing company.

Pay: $115,000.00 - $179,800.00 per year, * 401(k)

• Dental insurance
• Flexible schedule
• Health insurance
• Health savings account
• Life insurance
• Paid time off
• Parental leave
• Professional development assistance
• Tuition reimbursement
• Vision insurance

At eHub, we are revolutionizing fulfillment optimization for merchants and third-party logistics (3PL) providers. Our platform helps businesses streamline shipping, reduce operational complexity, and deliver exceptional customer experiences through smarter logistics technology.