Data Engineer

Company Description

At RIVO, you will find we recognize hard work and performance, foster a culture of growth, and encourage collaboration across departments. We value the unique skills and experiences that each employee brings to the table, recognizing that this diversity strengthens our company and helps us fulfill our core values: Respect, Integrity, Value, and Opportunity. If you share these same values and are eager to grow both personally and professionally, we encourage you to explore opportunities with us and apply today to join our dynamic team! 

Proud to be nationally recognized as a USA TODAY Top Workplace for 2026! Check out our other prestigious awards by clicking HERE!

Job Description

*This is a fully on-site role. Hybrid/remote work is not available at this time*
*We are unable to sponsor or take over sponsorship of an employment visa at this time*

RIVO is seeking an experienced Data Engineer to join our Data team and help build upon the infrastructure that drives analytics, reporting, and data‑driven decision‑making across the business.

As the team’s dedicated Data Engineer, this role offers a unique opportunity to own and shape data engineering at RIVO—working across multiple departments, gaining visibility with leadership, and building systems that directly impact the business. In this role, you’ll design and maintain scalable data pipelines, ensure data quality and reliability, and partner cross‑functionally to deliver production‑ready data solutions.

This is an ideal opportunity for someone who enjoys building robust data systems, solving complex data challenges, and contributing to a collaborative, high‑impact team environment.

Why You’ll Love Working Here

• High‑impact role supporting core analytics and business decision‑making
• Collaborative, cross‑functional team environment
• Opportunity to work on modern data infrastructure and scalable systems
• Ability to influence and improve data engineering best practices
• Strong visibility into how data drives business outcomes

What You’ll Do

• Build and maintain scalable ETL/ELT pipelines that move data from production systems into analytical environments
• Design and optimize data warehouse structures to support reporting, business intelligence, and analytics use cases
• Ingest and integrate data from multiple sources, including databases, APIs, and third‑party systems
• Develop and maintain data models that support efficient querying and downstream consumption
• Write and optimize complex SQL queries to transform, validate, and analyze data
• Establish data quality checks and monitoring processes to ensure accuracy, reliability, and completeness
• Partner with Engineering, Product, and Analytics teams to define data requirements and deliver trusted datasets
• Support Data Science and analytics initiatives by providing clean, structured, and accessible data
• Implement data governance best practices, including data security, access controls, and lifecycle management
• Troubleshoot data pipeline issues, performance bottlenecks, and data inconsistencies
• Continuously improve and automate data workflows to increase efficiency and reduce manual processes
• Provide technical guidance to team members through collaboration and code reviews, contributing to data engineering best practices and standards

Qualifications

What You Bring

• Bachelor’s degree in Computer Science, Information Systems, Mathematics, or a related field required
• 4–6+ years of experience in data engineering, data warehousing, or a related field
• Strong expertise in SQL, including complex queries and performance optimization
• Proficiency in Python (or similar language) for data processing and automation
• Experience building and maintaining production‑grade data pipelines and warehouse systems
• Experience integrating data from multiple sources into analytical environments
• Familiarity with data modeling, ETL/ELT processes, and pipeline orchestration
• Experience with data quality validation, monitoring, and troubleshooting
• Strong analytical and problem‑solving skills with attention to detail
• Ability to communicate technical concepts clearly across both technical and non‑technical audiences
• Comfortable working in a fast‑paced environment with evolving priorities

Additional Information<