Sr. Clinical Data Engineer

MiniMedNorthridge, CaliforniaOn-siteFull-timeMid level, 2–5 yearsListed 1 hour ago

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About this role

We anticipate the application window for this opening will close on - 1 Dec 2026

Responsibilities may include the following and other duties may be assigned.

- Design, develop, evaluate, and maintain data pipelines, programs, and workflows used to process, validate, and analyze clinical and medical device data.
- Build and support automated ETL/ELT solutions using Databricks, PySpark, SQL, and AWS services to ingest and transform structured and semi-structured data, including JSON and CSV files.
- Collect, clean, transform, and standardize raw clinical and device data into high-quality, analysis-ready datasets for statistical analysis and reporting.
- Partner with Biostatistics and study teams to understand analytical requirements and deliver finalized datasets optimized for statistical software and downstream use.
- Collaborate with Medical Device and Software Engineering teams to align on data schemas, firmware updates, data payload specifications, and system integration requirements.
- Identify data inconsistencies, perform root cause analysis, and implement solutions to ensure data quality, accuracy, and completeness.
- Support clinical data management activities, including data mining, validation, reconciliation, and issue resolution across multiple data sources.
- Contribute to the development and execution of data management plans that support study, project, and protocol timelines.
- Provide technical support for software user acceptance testing and review training materials, instructions, and documentation related to clinical data systems.
- Serve as a liaison among Clinical Research, R&D, Biostatistics, and other cross-functional stakeholders to communicate timelines, requirements, and deliverables.
- Apply software engineering best practices, including version control, CI/CD, and code review processes, to ensure reliable and maintainable solutions.
- Work independently on multiple projects in a deadline-driven environment while maintaining a high level of quality and accountability.
- Develop and evaluate algorithms to characterize product/system performance, quality, data management, and accuracy.
- Uses current programming language and technologies to translate algorithms and technical specifications into code.
- Completes programming and implements efficiencies, performs testing and debugging.
- Completes documentation and procedures for installation and maintenance.
- Can work with large scale computing frameworks, data analysis systems, and modeling environments.

TECHNICAL SPECIALIST CAREER STREAM:

- An individual contributor with responsibility in our technical functions to advance existing technology or introduce new technology and therapies.
- Formulates, delivers and/or manages projects assigned and works with other stakeholders to achieve desired results.
- May act as a mentor to colleagues or may direct the work of other lower-level professionals. Most of the time is spent delivering and overseeing projects – from design to implementation - while adhering to policies, using specialized knowledge and skills.

Required Knowledge and Experience:

- SQL:  Advanced proficiency - complex joins, window functions, CTEs, query optimization

- Data Warehousing:  Hands-on experience with platforms such as Snowflake, Databricks, BigQuery, Redshift, or Azure Synapse

- Python:  Proficient in pandas, NumPy, and data visualization libraries (matplotlib, seaborn, plotly ) .
- BI Tools:  Experience with Power BI
- Requires practical knowledge and demonstrated competence within job area typically obtained through advanced education combined with experience.
- Bachelor’s degree in computer science, Data Engineering, Biomedical Engineering, Statistics, or a related field with 4 years of relevant experience in clinical data engineering, clinical data management, data analytics, or a related technical field or 2 years with master’s degree.

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Preferred Qualifications:

- Education:  Bachelor’s degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or related field

- Experience:  3-5 years (1-3 years if master’s degree) of hands-on experience deriving insights and driving decisions from large, complex datasets
- Statistics:  Solid working knowledge of foundational statistical concepts such as hypothesis testing, distributions, regression, sampling methods, multivariate analysis, survival analysis, or statistical process control
- Communication:  Ability to translate technical findings into clear, actionable insights for cross-functional audiences

- Data Pipelines:  Familiarity with ETL/ELT workflows and pipeline tooling
- MedTech / Healthcare:  Experience or genuine interest in medical technology, clinical studies, or healthcare data - strongly preferred

- Data Storytelling:  A passion for turning complex data into compelling narratives that drive action - strongly preferred

- AI Dev Tools:  Experience with AI-assisted coding environments such as Amazon SageMaker Unified Studio, GitHub Copilot, or similar

- BI Tools:  Experience with Power BI, Tableau, or similar dashboard/reporting platforms

DIFFERENTIATING FACTORS

Autonomy:

- Established and productive individual contributor. Works independently with general supervision on larger, moderately complex projects / assignments.

Organizational Impact:

- Sets objectives for own job area to meet the objectives of projects and assignments. Contributes to the completion of project milestones. May have some involvement in cross functional assignments.

Innovation and Complexity:

- Problems and issues faced are general and may require understanding of broader set of issues or other job areas but typically are not complex. Makes adjustments or recommends enhancements in systems and processes to solve problems or improve effectiveness of job area.

Communication and Influence:

- Communicates primarily and frequently with internal contacts. External interactions are less complex or problem solving in nature. Contacts others to share information, status, needs and issues in order to inform, gain input, and support decision-making.

Leadership and Talent Management:

- May provide guidance and assistance to entry level professionals and / or employee in Support Career Stream.