We are looking for a Data Engineer to create and enhance scalable data solutions that strengthen business intelligence capabilities across the organization. This role partners with technology leaders, software teams, delivery stakeholders, and external partners to turn business needs into reliable technical outcomes. The position is well suited to someone who thrives in an agile setting, works confidently with minimal supervision, and collaborates effectively across teams. This opportunity is based in Nashville, Tennessee.
Responsibilities:
- Build and refine scalable data pipelines and platform components that support reporting, analytics, and enterprise intelligence initiatives.
- Assess modern cloud and big data technologies, gain working knowledge of new tools quickly, and recommend practical options based on business needs.
- Translate technical and business requirements into clearly defined tasks, implementation plans, and measurable deliverables.
- Write maintainable, efficient, and high-quality code that supports stable and dependable data solutions.
- Review existing processes and code for gaps or performance issues, then propose and implement improvements.
- Adjust priorities effectively in response to evolving project demands, timelines, and stakeholder expectations.
- Take ownership of delivered solutions by documenting design decisions and explaining functionality to team members and partners.
- Contribute to additional data engineering efforts that advance organizational goals and strengthen outcomes for end users.
- At least 5 years of experience working with data engineering platforms, tools, or related enterprise data technologies.
- At least 3 years of experience developing solutions with Python.
- At least 5 years of experience with databases or data tooling, including strong knowledge of data modeling principles.
- Demonstrated hands-on success delivering solutions within cloud-based infrastructure environments.
- Experience building or supporting data integration and ETL workflows using tools such as Azure Data Factory.
- Proficiency with SQL and the ability to work across complex data environments.
- Experience with Azure Databricks is preferred.
- Familiarity with Spark, Delta tables, and modern lakehouse or medallion architectural patterns is preferred.