Sr. Data Engineer with Snowflake, DBT & Python Skills

We are seeking an experienced Senior Data Engineer with strong expertise in Snowflake, dbt, and Python to design, develop, and maintain data pipelines and analytics frameworks across large-scale data environments. The ideal candidate will bring hands-on experience in building efficient ETL processes, data modeling, and performance optimization across public cloud environments. Experience in the healthcare domain is a strong plus. Key Responsibilities • Design, build, and maintain robust ETL/ELT pipelines using dbt and Snowflake for structured and semi-structured data sources. • Develop efficient and reusable data models following data warehouse best practices and ensure adherence to data governance standards. • Write high-quality, maintainable Python code to automate data workflows, transformations, and integrations with APIs or other data systems. • Implement data quality checks, monitoring, and alerting to ensure reliability and accuracy of datasets. • Collaborate with analytics, data science, and product teams to translate business requirements into scalable data models and transformations. • Optimize Snowflake environments for cost, query performance, and storage utilization. • Leverage cloud-native tools (AWS/GCP/Azure) for orchestration, data ingestion, and integration across systems. • Contribute to architectural discussions and implement best practices for version control, CI/CD, and deployment automation for dbt projects. • Ensure compliance with data privacy and security policies, particularly in regulated industries like healthcare (HIPAA, PHI, etc.). Required Skills & Qualifications • 6+ years of hands-on experience with Snowflake, including performance tuning, role-based access control, and data modeling. • 6+ years of experience in dbt (data transformations, testing, documentation, deployment). • Strong background in ETL/ELT design, implementation, and orchestration. • 6+ years of experience in Python for data engineering tasks, including API integration and automation. • Solid understanding of data warehousing concepts, dimensional modeling (star/snowflake schema), and data lake architectures. • Experience working with at least one public cloud platform (AWS, Azure, or GCP) and familiarity with services like AWS Lambda, S3, Glue, GCP BigQuery, or Azure Data Factory is advantageous. • Strong SQL skills and the ability to optimize complex queries. • Excellent communication and problem-solving skills. Nice to Have • Prior experience in healthcare data (e.g., EMR/EHR, claims, HL7/FHIR formats, HIPAA compliance). • Exposure to data observability or lineage tracking tools.