Design, develop, and maintain scalable ETL/ELT pipelines that support cross-functional data needs
Build, deploy, and optimize Power BI dashboards and other reporting tools to support strategic decision-making
Write well-structured, testable code in Python, R, and SQL to support analytics workflows
Lead the development and enforcement of version control, documentation, and coding standards
Partner with data scientists to bring analytics products from prototype to production
Identify and integrate AI-driven tools to enhance data processing and reporting capabilities
Mentor junior team members and contribute to a culture of knowledge sharing and continuous improvement

Requirements

Bachelor’s degree required; Master’s degree preferred in a technical field such as Computer Science, Engineering, Data Science, or related disciplines
3-5+ years of hands-on experience in a data engineering, analytics engineering, or data science role
Proficient in Python, R, SQL, and Power BI, with experience operationalizing analytics at scale
Strong experience with Git and collaborative development workflows
Experience designing data architectures and maintaining complex pipelines
Familiarity with Databricks and cloud platforms (e.g., AWS, Azure)
Interest or experience in applying AI to streamline or augment data workflows
Excellent communication skills with a demonstrated ability to work across technical and non-technical teams
Bonus: Experience working with patient-level data or in regulated environments (e.g., HIPAA, GxP, FDA)

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

ETLELTPythonRSQLPower BIGitdata architecturedata pipelinesAI-driven tools

Soft Skills

mentoringknowledge sharingcontinuous improvementcommunication