Data Warehouse Engineering Manager(REMOTE)

Job description:

• Lead, mentor, and develop a high-performing team of data engineers, fostering an engineering culture centered on collaboration, innovation, and continuous improvement.
• Architect, design, and manage data warehouse and lakehouse solutions on Databricks and Azure, ensuring scalability, security, and compliance with healthcare regulations.
• Evaluate and implement AI and machine learning technologies within Databricks and Azure environments to optimize data processes and accelerate analytics capabilities.
• Implement DevSecOps principles across the data engineering environment, integrating security, compliance, and automation into every stage of the development lifecycle.
• Develop and manage CI/CD pipelines for data engineering workflows to promote automated testing, deployment, and environment consistency.
• Drive automation across data ingestion, transformation, and quality frameworks to deliver efficient, robust, and scalable data processes.
• Collaborate with Analytics, IT, and business partners to deliver secure, efficient, and compliant data warehouse solutions that meet organizational data needs.
• Oversee data modeling, integration, governance, and data quality frameworks that ensure accuracy, consistency, and business trust in analytic data sets.

Qualifications:

• Bachelors or masters degree in computer science, information systems, data engineering, or related field.
• Minimum of seven (7) years of experience in data engineering or data warehouse architecture, including at least three (3) years in a technical leadership position.
• Two (2) years of supervisory experience with demonstrated ability to mentor and develop team members.
• Deep expertise in Databricks architecture including Delta Lake, Apache Spark, and MLflow, with strong experience implementing complex data pipelines and transformations.
• Hands-on experience architecting and deploying analytics and data infrastructure on Microsoft Azure (Data Factory, Azure SQL, Storage, etc.).
• Proven experience implementing DevSecOps frameworks, secure data operations, and governance in regulated industries - healthcare experience strongly preferred.
• Strong understanding of CI/CD, infrastructure-as-code, and automation tools such as GitHub Actions, Azure DevOps, or equivalent technologies.
• Experience integrating AI and machine learning capabilities to streamline data workflows and enhance analytical insights.

Why is This a Great Opportunity:

• Lead, mentor, and develop a high-performing team of data engineers, fostering an engineering culture centered on collaboration, innovation, and continuous improvement.
• Architect, design, and manage data warehouse and lakehouse solutions on Databricks and Azure, ensuring scalability, security, and compliance with healthcare regulations.
• Evaluate and implement AI and machine learning technologies within Databricks and Azure environments to optimize data processes and accelerate analytics capabilities.
• Implement DevSecOps principles across the data engineering environment, integrating security, compliance, and automation into every stage of the development lifecycle.
• Develop and manage CI/CD pipelines for data engineering workflows to promote automated testing, deployment, and environment consistency.
• Drive automation across data ingestion, transformation, and quality frameworks to deliver efficient, robust, and scalable data processes.
• Collaborate with Analytics, IT, and business partners to deliver secure, efficient, and compliant data warehouse solutions that meet organizational data needs.
• Oversee data modeling, integration, governance, and data quality frameworks that ensure accuracy, consistency, and business trust in analytic data sets.

Salary Type : Annual Salary

Salary Min : $ 132181

Salary Max : $ 174478

Currency Type : USD