Senior Data Engineer

About Revecore 

Revecore is an innovative, technology-driven company that is committed to helping our clients, our employees, our company, and our communities thrive.

With a 20+ year history, Revecore is the leading provider of revenue integrity and complex claims solutions for hospitals.

We offer a dynamic and flexible work environment, full of opportunities for motivated, hands-on team players. We strive each day to solve complex business problems and find new ways to enhance the efficiency, effectiveness, and quality of our services. If those attributes resonate with you, regardless of where you are located—we want you on our team! 

Purpose of this Role 

Revecore is embarking on re-architecting and modernizing its core platform. The Data Technology at Revecore is empowering the business in unlocking new opportunities by integrating data and machine learning across our products and business functions. This team is composed of Data Engineering, Analytics Engineering, Data Science and Machine Learning (ML) Engineering specializations. 
 

The Senior Data Engineer will join the Technology function, solving complex data problems for the Revecore Data Platform. The ideal candidate is capable of contributing to platform, architecture, and automation best practices, while also diving deep into specific areas and finding the best path forward. You are expected to pave the path for the data teams around data ingestion, data pipelines and data operations. You will be responsible for building a modern data lakehouse platform that will transform Revecore and its capabilities. 

What You'll Do 

• Own the implementation and quality of the data platforms, ensuring availability, reliability, resilience, and security while upholding consistent standards of engineering excellence. 

• Continuously improve both the engineering practice and the quality of the domain’s data outputs. 

• Design and develop scalable, maintainable, and reliable data pipelines to support business and analytics needs. 

• Collaborate with other Data Engineers to understand requirements and build tooling and automation that enhance developer efficiency. 

• Monitor data systems and performance, identifying opportunities to optimize warehouse and infrastructure costs. 

• Stay current with industry trends and emerging technologies across the data platform ecosystem to drive innovation and modernization. 

Requirements 

• 5+ years of experience designing and deploying data engineering solutions using Python, SQL, and modern orchestration/transformation frameworks (e.g., dbt, Airflow, Dagster, Prefect). 

• Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience). 

• Experience designing, building, and maintaining scalable, reliable data pipelines with containerized deployments on Kubernetes or Docker. 

• Experience with modern data warehouses such as Snowflake, Redshift, or BigQuery. 

• Proven ability to develop and support multi-cloud data platforms on Azure and AWS, including data lakes (ADLS, S3) and data warehouses (Synapse, Snowflake, Redshift); automate infrastructure using Terraform or CloudFormation. 

• Expertise in pipeline optimization for performance, cost efficiency, and reliability using monitoring (Prometheus, Grafana), CI/CD (GitHub Actions, Jenkins), and data quality frameworks. 

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