Staff Data Engineer

• Comprehensive medical, dental, vision, and life insurance benefits from the start of your employment 
• 12 paid holidays and flexible paid time off    
• 401(k) contributions   
• Employee Resource Groups that build community  
• Career growth opportunities   
• An excellent work/life balance 

Overview 

The Staff Data Engineer will serve as a senior technical leader within Revecore’s Technology function, driving architectural decisions, platform modernization, and engineering excellence across the data ecosystem. This role is pivotal in shaping the future of Revecore’s data infrastructure, enabling scalable, secure, and efficient data operations working across Mint, Cura, and Bridge systems. A key responsibility of this role is to lead the migration and rationalization of legacy, homegrown tooling, infrastructure, and codebases—bringing clarity, structure, and modernization to historically complex or bespoke systems. 

Key Responsibilities 

• Platform Leadership: Own the quality and reliability of Revecore’s data platforms, ensuring high standards for availability, resilience, security, and scalability. 

• Architecture & Design: Define and evolve the architecture of data systems, including a modern data lakehouse strategy. 

• Legacy Modernization: Assess, deconstruct, and lead the migration of legacy homegrown tools, infrastructure, and codebases into scalable, maintainable, and cloud-native solutions. 

• Technical Guidance: Mentor senior engineers and collaborate with managers and technical leads to align engineering decisions with business goals. 

• Pipeline Development: Build and maintain scalable, maintainable, and reliable data pipelines for ingestion, transformation, and modeling. 

• Cross-Functional Collaboration: Partner with Analytics Engineers, ML Engineers, and Data Scientists to deliver tooling and automation that improves developer efficiency. 

• Cost Optimization: Monitor system performance and identify opportunities to reduce infrastructure and warehouse costs. 

• Innovation & Thought Leadership: Lead vision-setting for data systems and stay ahead of industry trends in data architecture and governance. 

• Quality & Standards: Champion engineering best practices and drive continuous improvement in code quality and deployment safety. 

Experience Requirements 

• 10+ years of professional experience in data engineering, software engineering, or platform development, with a strong track record of technical leadership and architectural ownership. 

• 5+ years of experience designing and building large-scale data platforms and pipelines in cloud environments. 

• Prior experience modernizing legacy systems, including homegrown tools and infrastructure, is highly desirable. 

• Experience in the Healthcare and/or Revenue Cycle Management domain is a plus but not required. 

• Proven ability to lead cross-functional initiatives and influence technical direction across teams. 

Qualifications 

• Proven experience with data warehousing, data lakes, ELT, and streaming platforms (e.g., Azure Synapse, Snowflake, Redshift). 

• Strong cloud expertise (Azure or AWS). 

• Advanced proficiency in SQL for data manipulation, analysis, and modeling, along with strong programming skills in Python. 

• Deep knowledge of .NET Framework and .NET Core. 

• Experience with Infrastructure as Code (Terraform, CloudFormation). 

• Familiarity with CI/CD pipelines and workflow automation (Azure Pipelines, GitHub Actions, Jenkins). 

• Exposure to tools such as dbt, Airflow, Kubernetes, Docker. 

• Strong understanding of the data SDLC and deployment practices. 

• Demonstrated ability to drive technical change and influence architectural direction. 

• Bachelor’s or Master’s degree in Computer Science or equivalent experience. 

• A quiet, distraction-free environment to work from in your home.   
• A secure home internet connection with speeds >20 Mbps for downloads and >10 Mbps for uploads is required. 
• The workspace area accommodates all workstation equipment and related materials and provides adequate surface area to be productive.