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# Senior Data Engineer

- **Company:** Solventum Corporation
- **Location:** Maplewood, MN, United States (Remote available)
- **Experience:** Expert
- **Salary:** $143,200.0 - $196,900.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Automation of Tests, Microsoft Azure, Cloud Computing, Information Systems, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Systems, Software Debugging, Decision Support Systems, Dimensional Modeling, Github, Python (Programming Language), Machine Learning, Microsoft Visual Studio, Power BI, Cloud Services, Software Deployment, SQL Stored Procedures, SQL Databases, Tableau (Software), Sql Optimization, Retrieval-Augmented Generation, Snowflake, Data Layers, Semi-structured Data, Data Lineage, Database View, Software Version Control
- **Published:** October 28, 2026
- **Apply:** https://www.disabledperson.com/jobs/76247472-senior-data-engineer

## About the Role

* Bachelor's Degree or higher AND eight (8) years of professional experience in data engineering, data architecture, analytics engineering, information systems, or analytics application development in a private, public, government, or military environment, * High School Diploma/GED AND twelve (12) years of professional experience in data engineering, data architecture, analytics engineering, information systems, or analytics application development in a private, public, government, or military environment, * Five (5) years of hands-on experience developing complex SQL, analytical data models, and production ETL/ELT solutions in a cloud data warehouse environment.
 * Three (3) years of experience designing dimensional models, semantic layers, reusable reporting datasets, or governed business metrics for enterprise analytics.
 * Three (3) years of experience with version-controlled development, automated testing, controlled deployments, and production support for data solutions.

 * Three (3) years experience translating complex business requirements and rules into reliable technical solutions while communicating effectively with technical and nontechnical stakeholders.

Additional qualifications that could help you succeed even further in this role include:

 * Experience using AI-assisted development tools responsibly, including validation of generated code, recommendations, tests, and documentation before production use.
 * Advanced experience with Snowflake, SQL, Python, dbt or a comparable transformation framework, GitHub, Visual Studio Code, and cloud platforms such as Azure or AWS.

 * Experience creating automated reconciliation, data-quality, observability, or validation solutions and optimizing SQL or warehouse workloads for performance and cost.
 * Experience enabling Tableau, Power BI, natural-language analytics, machine learning, retrieval-augmented generation, or agent-based solutions through trusted and governed data products.
 * Experience supporting order-to-cash, revenue cycle, billing, collections, productivity, customer service, healthcare, medical technology, or other regulated commercial operations.
 * Demonstrated technical leadership through mentoring, engineering standards, architecture decisions, or coordination of complex cross-functional data deliveries.

## Description

As a Senior Data Engineer supporting Commercial Operations Analytics, you will have the opportunity to tap into your curiosity and collaborate with some of the most innovative and diverse people around the world. You will design trusted data products for order-to-cash reporting, operational dashboards, scorecards, productivity measurement, and AI-enabled decision support. Here, you will make an impact by:

 * Designing and maintaining scalable analytical data models, semantic layers, reporting tables, views, and business definitions for productivity, unbilled activity, write-offs, accounts at risk, payer segmentation, organizational hierarchies, and other commercial operations measures.
 * Building and optimizing reliable ETL/ELT workflows, SQL transformations, database views and tables, stored procedures, and scheduled processes that integrate structured and semi-structured data into analytics-ready products using platforms such as Snowflake and cloud services.
 * Creating automated data-quality and regression-testing frameworks that encode business rules, reconcile results to authoritative sources, identify anomalies, and protect existing models when changes are introduced.
 * Owning delivery from requirements through development, version control, peer review, validation, user approval, production deployment, monitoring, and post-production issue resolution while documenting data lineage, definitions, dependencies, and support procedures.
 * Using approved AI assistants and focused engineering agents to accelerate SQL analysis, code development, pipeline configuration, debugging, documentation, and test creation, while applying human review for accuracy, security, performance, governance, and business-rule fidelity.