Senior Software Engineer – ETL and Python

Primary Responsibilities:

1. Design, develop, and maintain ETL pipelines using SSIS and SQL Server
2. Build scalable and reusable data processing scripts in Python for analytics and automation
3. Collaborate with data scientists and AI engineers to support model development, deployment, and monitoring
4. Ensure data quality, lineage, and compliance with internal and external governance standards
5. Work with healthcare data formats and standards (e.g., HL7, FHIR, ICD-10) to support clinical and operational use cases
6. Participate in data architecture design, including data lakes, warehouses, and marts
7. Support metadata management, data cataloging, and access control initiatives
8. Apply basic AI/ML techniques for data enrichment, anomaly detection, and predictive modeling
9. Document technical processes, data flows, and governance policies
10. Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

1. 2+ years of experience in SQL and SSIS for ETL and data integration
2. Experience with data modeling, data warehousing, and performance optimization
3. Proficiency in Python for data manipulation, scripting, and automation
4. Understanding of AI/ML fundamentals (e.g., classification, regression, clustering)
5. Familiarity with data governance principles (e.g., data stewardship, privacy, compliance)
6. Solid problem-solving and analytical skills
7. Proven excellent communication and collaboration abilities

Preferred Qualifications:

1. Certifications in Data Engineering, AI/ML, or Healthcare IT
2. Experience with cloud platforms (Azure) and data services
3. Exposure to healthcare data systems and standards
4. Familiarity with AI model lifecycle management