Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading healthcare organization is seeking a Sr. Enterprise Data Engineer to support enterprise-wide data and analytics initiatives. The organization focuses on using technology, data, and innovation to support informed decision-making and improve operational outcomes across its healthcare environment.
Key Responsibilities
- Collaborate with organizational leaders and users to design, test, and implement complex data stores, pipelines, and related data solutions based on business requirements.
- Research, develop roadmaps for, and maintain standard data modeling, DevOps, and development tools and processes.
- Explore emerging technologies and develop innovative solutions that improve development and operational efficiency.
- Independently perform analysis, development, and testing of complex data marts and enterprise data solutions.
- Support other data engineers in designing and implementing complex data solutions.
- Promote the use of data solutions to support data-driven decision-making.
- Apply advanced knowledge across multiple data domains to develop high-quality enterprise solutions.
- Build strong working relationships with users, team members, directors, and senior stakeholders.
- Participate as a technical data steward in metadata management, data quality, and other data governance activities.
- Assist in identifying and resolving data quality issues.
- Manage multiple complex activities, tasks, dependencies, project scopes, and delivery timelines.
- Provide project management and project leadership when necessary to drive project timelines and deliverables across multiple departments and functions.
- Participate in project working groups involving team members, users, analysts, clinicians, and organizational leadership.
- Lead teams in defining design and development standards and conduct peer reviews to ensure compliance with established standards.
- Define analytics standards and best practices and support business data analysts in adopting these standards.
- Participate in analytics community meetings and contribute to the advancement of organizational analytics practices.
- Tune the performance of complex data solutions.
- Troubleshoot incidents, conduct root cause analysis, and establish countermeasures to improve supported solutions.
- Identify opportunities to improve data engineering, analytics, development, and operational processes.
Required Qualifications
- Bachelor’s degree in Information Technology, Information Systems, Business Management, Business Analytics, Business Administration, or a directly related field from an accredited college or university.
- 7 or more years of experience in reporting, analytics, business intelligence, or healthcare technology.
- Alternatively, 3 or more years of development experience with cloud data lake technologies, such as PySpark notebooks or pipelines on Databricks, utilizing DevOps, CI/CD, and orchestration processes.
- Advanced knowledge of relational database concepts and database design.
- Advanced data modeling skills with the ability to translate business requirements into logical and physical database designs for moderate to large complex projects.
- Experience developing solutions using cloud data platforms such as Azure and Databricks.
- Experience with technologies including PySpark, notebooks, GitHub, and related development tools.
- Ability to deploy production solutions in a secure and highly automated environment.
- Expert knowledge of SQL.
- Ability to relate and work with data across multiple data domains.
- Expert knowledge of standard development and design tools and general DevOps concepts and practices.
- Ability to tune the performance of moderately complex solutions.
- Strong troubleshooting and root cause analysis capabilities.
- Ability to work independently with limited direct supervision.
- Ability to provide regular updates regarding pending tasks, challenges, and potential roadblocks.
- Demonstrated ability to successfully complete complex projects.
- Ability to produce high-quality work with minimal defects across moderate to complex solutions.
- Strong presentation skills, with the ability to communicate moderately complex concepts to a variety of audiences, including senior managers and industry groups.
- Effective verbal, written, and interpersonal communication skills.
- Ability to understand how data engineering and technology initiatives contribute to broader organizational goals and identify opportunities for improvement.
Disclaimer
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