Data Engineer / Data Analyst

About the job

At Redefine Healthcare, we believe in providing all patients with the highest quality of care and compassion. With our dedicated team of Neurosurgeons, Interventional Pain Management Specialists, Orthopedists, Psychiatrists, Physical Therapists, and Chiropractors, we pride ourselves on specializing in continuity of care for our patients. We are excited to add Vascular to our growing list of specialties.

Redefine Healthcare is looking for a dedicated, full-time Data Engineer / Data Analyst to join our expanding team of healthcare professionals in our Matawan Office. The ideal candidate will be responsible for producing and managing weekly reports in Excel, preparing findings for stakeholder distribution, and supporting a variety of special projects. This includes handling ad hoc data requests and contributing to efforts to optimize and automate reporting workflows using SQL and Python. We are looking for candidates who are motivated, compassionate, and are looking to advance their career in a community that is always growing.

Job Title: Data Engineer / Data Analyst

Salary/Pay Rate: $110,000-130,000, depending on specialty and experience

Hours: 40 hours per week

Job Type: Full-time

Benefits: Paid time off, sick time, health insurance (medical, dental, vision, accident, and critical illness), life insurance, 401(k) with Company match, yearly bonus

Position Overview

The Data Engineer / Data Analyst will:

• Own the design and build of our data warehouse and ETL pipelines from our Snowflake environment into our internal warehouse.
• Continue to perform traditional data analyst responsibilities, including producing weekly reports in Excel, preparing findings for stakeholders, and supporting special projects.

We are looking for someone who can move comfortably between building data infrastructure and delivering clean, reliable reporting for clinical, operational, and financial leaders.

Key Responsibilities:

Data Engineering

• Design, build, and maintain ETL pipelines to an internal data warehouse.
• Build a database from scratch, including data models, schemas, and table structures that support reporting and analytics needs.
• Develop and maintain SQL scripts, jobs, and workflows to extract, transform, and load data from multiple source systems.
• Implement data validation and quality checks throughout the pipeline.
• Work with stakeholders to understand reporting and analytics needs and translate them into robust data models.
• Monitor pipeline performance and troubleshoot data or performance issues.

Data Analytics

• Develop, maintain, and deliver recurring reports (primarily in Excel) on a weekly basis.
• Prepare and present key findings and insights for internal stakeholders.
• Respond to ad hoc data requests with timely, accurate analysis.
• Collaborate on special projects focused on improving analytics capabilities and operational visibility.
• Use SQL to extract, manipulate, and validate data from the warehouse and other databases.
• Apply Python scripting to automate routine tasks, streamline reporting, and support data engineering workflows.
• Identify data quality issues and work cross-functionally to address them.
• Continuously improve data processes, documentation, and reporting efficiency.

Minimum Education and Experience

• Bachelor’s degree in a quantitative field
•  (Statistics, Economics, Computer Science, Mathematics, Data Science, Business Analytics, or related field).
• Prior experience as a data analyst in the healthcare industry is strongly preferred.
• 3+ years of experience in a data analyst, data engineer, or hybrid analytics/engineering role.

Required Skills

• Strong proficiency in Microsoft Excel (pivot tables, lookups, charts, formulas, etc.).
• Advanced SQL skills for querying large datasets and building ETL processes.
• Hands-on experience with Snowflake or similar cloud data platforms.
• Experience designing and building ETL pipelines and working with data warehouses.
• Working knowledge of Python (Pandas, NumPy, or similar libraries) for data manipulation and automation.
• Experience working with structured data formats; familiarity with JSON or Parquet is preferred.
• Strong attention to detail and organizational skills.
• Ability to communicate findings clearly to both technical and non-technical audiences.
• Comfortable working in a hybrid role that includes both data engineering and reporting/analytics tasks.