Sr Data Engineer

We are seeking a Senior Data Engineer to design, build, and operate production-grade ETL/ELT pipelines across enterprise cloud platforms, primarily Google Cloud Platform (GCP) and Microsoft Azure. This role is responsible for end-to-end ownership of data pipelines-from requirements gathering and solution design through deployment, monitoring, and ongoing production support.

The ideal candidate is a hands-on technical leader who thrives in ambiguous environments, proactively drives solutions, and delivers scalable, secure, and reliable data systems within a healthcare ecosystem. This individual will partner closely with business stakeholders, architects, analysts, and engineering teams to transform complex requirements into production-ready data solutions., * Design, develop, deploy, and support scalable ETL/ELT pipelines across GCP, Azure, BigQuery, and SQL Server environments.

• Build and optimize analytical data models, including dimensional models, schema design, normalization strategies, and Slowly Changing Dimensions (SCDs).
• Develop and manage workflow orchestration solutions using Airflow, Cloud Composer, Azure Data Factory (ADF), Dagster, Prefect, or similar technologies.
• Ensure secure handling of Protected Health Information (PHI), including data movement, de-identification, access controls, auditing, and HIPAA compliance.
• Implement CI/CD deployment processes using Git and modern DevOps practices.
• Monitor, troubleshoot, optimize, and support production data pipelines to ensure reliability, performance, and scalability.
• Collaborate with business stakeholders to translate requirements into technical solutions and communicate tradeoffs, feasibility, risks, and recommendations.
• Drive technical decisions and establish direction when requirements are incomplete or evolving.
• Evaluate emerging technologies and modern data engineering approaches through proof-of-concepts and technical experimentation.
• Contribute to data engineering best practices, architecture standards, operational excellence, and continuous improvement initiatives.

• 7+ years of experience in Data Engineering, including significant experience delivering and supporting enterprise production systems.
• Strong SQL development skills combined with hands-on experience in Python or Java.
• Experience designing, building, and operating large-scale ETL/ELT pipelines in cloud environments.
• Hands-on expertise with GCP, Azure, BigQuery, SQL Server, or comparable enterprise data platforms.
• Experience with workflow orchestration tools such as Airflow, Cloud Composer, Azure Data Factory, Dagster, or Prefect.
• Strong data modeling experience, including dimensional modeling, normalization, star schemas, and Slowly Changing Dimensions (SCDs).
• Knowledge of healthcare data security practices, HIPAA regulations, PHI handling, access controls, auditing, and data governance.
• Experience implementing source control, Git workflows, and CI/CD deployment processes.
• Proven ability to deliver solutions within enterprise governance, compliance, and operational standards.

Preferred Qualifications

• Experience supporting healthcare, life sciences, or other highly regulated industries.
• Exposure to modern ELT frameworks and cloud-native data architectures.
• Familiarity with semantic layers, modern analytics platforms, and enterprise reporting ecosystems.
• Understanding of LLM-assisted development tools and emerging AI-enabled data engineering practices.
• Experience evaluating and implementing new technologies through proof-of-concepts and technical pilots.