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Tier-1 brand and metro location increase competition despite seniority and niche healthcare data requirements.
High - demands healthcare-specific standards, compliance, and cloud data engineering expertise limiting transferability.
High - requires 9+ years, specific cloud/data stack, and healthcare compliance expertise.
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Lead design, development, and optimization of end-to-end cloud-native data ingestion, ETL/ELT pipelines, and workflows across Azure, GCP, and AWS environments.
Architect and manage large scale data warehouse and lakehouse solutions (Snowflake, BigQuery, Databricks) ensuring performance, scalability, and cost-efficiency.
Provide hands-on leadership, mentoring data engineers, prioritizing tasks, and ensuring timely delivery while enforcing data governance and healthcare regulatory compliance.
9+ years of experience in data engineering with cloud-native data pipelines focus.
Hands-on expertise with Snowflake, BigQuery, Databricks (PySpark, SQL), and healthcare data formats (FHIR, HL7, claims, EMR).
Proficiency in Azure and GCP cloud services including Data Factory, Synapse, Cloud Composer, Google Cloud Storage.
Experience with CI/CD, DevOps for data, infrastructure-as-code, plus communication and leadership skills.
Experienced in managing complex, large-scale cloud data platforms involving healthcare standards and regulations (HIPAA, HITRUST).
Strong leadership capability demonstrated by mentoring teams and coordinating cross-functional partnerships including clinical and analytics stakeholders.
Deep technical expertise in multi-cloud environments (Azure, GCP, AWS) and modern data engineering tools and orchestration frameworks (e.g., Airflow, dbt).