Senior Data Engineer

• →Required - Bachelor's Computer Science, Engineering, or related field.

Ochsner Health does not consider an individual an applicant until they have formally applied to the open position on this careers website.

Please refer to the job description to determine whether the position you are interested in is remote or on-site. Individuals who reside in and will work from the following areas are not eligible for remote work position: Colorado, California, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington, and Washington D.C.

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Ochsner is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any legally protected class, including protected veterans and individuals with disabilities.

• Required - 9 years Experience implementing data quality checks, security, and governance standards. Strong Health System domain knowledge with experience in exploratory data analysis
• Preferred - 10+ years Experience with multiple Cloud Platforms (Azure, AWS, GCP) and related services
  Experience working in an agile/scrum environment.

• Excellent analytical and problem-solving skills.
• Strong communication and ability to convey complex concepts simply.
• Ability to work independently and also work collaboratively in a team environment.
• Ability to mentor and support peers on technical topics.
• Strong knowledge of Epic Clarity/Caboodle data models.
• Hands-on data acquisition/integration experience designing, building, implementing and optimizing cloud data warehouse solutions.
• Strong experience in data engineering tools such as DBT and Azure Data Factory on Snowflake/Azure and orchestration tools like Airflow.
• Proficiency in programming languages such as Python or Scala, SQL, data modeling, ETL/ELT development, orchestration frameworks, and cloud platforms and related services (Data Lake Storage, Secrets management, Authentication methods).
• Proven Experience in designing complex data models to connect data across multiple domains.
• Strong understanding of DevOps practices, CI/CD, version control, and automation frameworks.

• Designs, builds, and optimizes scalable data pipelines for structured and unstructured data ingestion.
• Develops and maintains monitoring, automation, and performance tuning processes to ensure data reliability.
• Applies best practices in data modeling, ETL/ELT, and transformation to deliver secure, high-performance solutions.
• Designs and standardizes cross-domain data models to enable consistent, enterprise-wide analytics.
• Translates business requirements into scalable, secure, and value-driven technical solutions.
• Selects and implements appropriate technologies across databases, streaming, orchestration, and cloud platforms.
• Identifies and recommends opportunities to leverage AI/ML to advance data solutions.       
• Contributes to CI/CD pipelines and drives automation to improve operational efficiency.
• Ensures data quality, integrity, security, and compliance; proactively monitors and remediates risks.
• Collaborates with stakeholders, mentors junior engineers, and drives continuous improvement through code reviews and solution evaluation.
• Performs other duties as assigned
• Complies with all policies and standards