Data Engineer

Description
We are looking for a Data Engineer to join a collaborative technology team in Nashville, Tennessee, where you will help shape reliable, scalable data solutions that support critical business and healthcare-focused initiatives. This role is ideal for a hands-on builder who enjoys working across technical and business groups to turn complex needs into well-architected platforms and efficient data workflows. You will contribute in an agile setting, partner with stakeholders across the organization, and play a key role in improving data quality, performance, and delivery.

Responsibilities

Build and enhance scalable data pipelines and modular processing frameworks that strengthen business intelligence and analytics capabilities. Work with cloud and big data technologies to develop, tune, and support high-volume data platforms for enterprise use. Convert business goals and functional needs into technical plans, while identifying dependencies, constraints, and delivery risks early in the process. Produce clean, maintainable code and follow disciplined engineering practices for source control, testing, deployment, and documentation.

Partner with internal teams, leadership, and vendors to define requirements and design solutions that align with operational and strategic objectives. Improve pipeline reliability, system efficiency, and data processing performance through ongoing evaluation and optimization. Provide guidance to teammates by sharing practical knowledge of modern data engineering methods, tools, and development standards. Investigate production issues, resolve technical problems, and help maintain the stability and availability of data systems.

Communicate architectural decisions and implementation details clearly to both technical stakeholders and non-technical audiences. Requirements
At least 8 years of experience in data engineering or closely related platform development work. At least 8 years of experience with relational and non-relational databases, including data modeling, schema design, and query tuning. At least 5 years of experience building scalable solutions in Python or another object-oriented programming language.

Strong hands-on experience with Databricks, Spark, and Delta tables in distributed data processing environments. Working knowledge of Lakehouse and Medallion architectural patterns. Experience creating data integration and ETL pipelines with Azure Data Factory or a comparable tool. Proven background deploying and supporting cloud-based data solutions, preferably in Microsoft Azure, with attention to monitoring, security, and cost management. Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field. Technology Doesn't Change the World, People Do.

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