Data Engineer

We are seeking an experienced Data Engineer with a strong background in healthcare data integration, cloud platforms, and Salesforce data ecosystems. The ideal candidate will have proven expertise in building and optimizing scalable, secure, and high-performance data pipelines that power analytics, reporting, and patient engagement workflows.

Minimum Experience Requirements

Advanced Data Integration (5+ years):

• Strong experience integrating data from healthcare systems, Salesforce, and cloud-based sources.
• Expertise in managing complex data pipelines for large-scale data ingestion and transformation.
• Hands-on experience integrating Salesforce data using MuleSoft, Salesforce APIs, and Data Loader.
• Deep understanding of how Salesforce data supports patient engagement, clinical workflows, and reporting.

Cloud Platform Expertise (5+ years):

• Proven experience with AWS services (S3, Redshift, Glue, Lambda, Athena, EC2) for data storage, processing, and orchestration.
• Experience scaling cloud infrastructure to manage large and sensitive healthcare datasets.

Healthcare Data Experience (3+ years):

• Strong background working with healthcare data (clinical data, patient records, lab results).
• Familiarity with healthcare data integration and regulatory standards such as HIPAA.
• Bachelor’s or Master’s Degree in Computer Science, Data Engineering, Health Informatics, or a related field.
• Equivalent practical experience may also be considered.

Required Skills:

• Expertise with AWS data services (S3, Redshift, Glue, Lambda, Athena, EMR).
• Ability to architect and optimize data pipelines for performance, scalability, and reliability.
• Proficiency in integrating Salesforce data via APIs.
• Strong ETL/ELT experience with AWS Glue, Apache Airflow, or custom Python scripts.
• Knowledge of healthcare data security standards (HIPAA, HITECH), encryption techniques, and secure data transfer.
• Hands-on experience with AWS Redshift or Snowflake for building high-performance data warehouses, enabling efficient querying and BI accessibility.
• Proven collaboration with BI and analytics teams to translate business requirements into technical solutions and ensure data supports actionable insights.