Data Engineer at UBDS Group focusing on designing and optimizing modern data platforms. Collaborating in a multidisciplinary team to develop reliable data assets for analytics and operational use cases.
About the role
- Data Engineer responsible for developing research analytic data infrastructure at Sutter Health. Involves managing data quality, pipelines, and compliance with healthcare regulations.
Responsibilities
- Responsible for developing Sutter Health’s research analytic data infrastructure.
- This includes all aspects of how data is ingested, stored, collected, governed, cleansed, accessed, and used.
- Utilizes tools and infrastructure such as scalable data pipelines to manage high volume and high-speed data storage and retrieval, as well as automated testing and tools for improving data quality.
- Works with all types of data including batch and streaming data, structured, semi-structured and unstructured data, files, web downloads, and other sources of data.
- Creates and improves processes required by other data-dependent function including analytics, strategic business intelligence, and data science.
- Uses state-of-the-art methods to capture, route and store data, combining information from different sources, transforming it to improve the data’s reliability, quality and usability.
- Develops and tests new architectures that enable data extraction, automation, and modeling for predictive or prescriptive analytic purposes.
- Sets the standard for high-value high quality datasets that are accurate, timely, secure and well-suited to strategic analytic purposes research organization.
- Work on IRB approved research studies providing accurate and timely curated data.
- Work closely with Principal investigators and statisticians.
- Work in accordance with Research Privacy and HIPAA regulations and methods for safeguarding PHI and PII.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Management, or Healthcare Administration
- 8 years recent relevant experience
- Experience creating data pipelines on big data platforms and data integrations in databases and data lakes, working with various cloud and on-premises technologies.
- Experience leveraging scalable data platforms to build secure infrastructure; experience building batch or streaming data ingestion pipelines.
- Ability to assess and profile raw data and reassemble raw data from multiple sources into a single, enterprise model.
- Hands on experience with data management tools (Cloudera, Spark, Python, Databricks, etc.); fluency with SQL programming, scripting, and data architecture.
- Extensive familiarity with relational database concepts / technologies (SQL, Oracle, etc.) including data design, table design, partitioning, as well as determining the technology to use in any given scenario.
- Experience ensuring data quality and implementing tools and frameworks for automating identification of data quality issues.
- Strong understanding of data engineering and data traceability best practices and framework
- Ability to work in a consulting role, building technology and communicating with end-users and customers of varying levels of technical capability.
- Strong knowledge in the development of Business Intelligence and Reporting solutions.
- Ability to translate data into Management reports and presentations.
- Strong problem solving, organization, and prioritization skills.
- Detail-oriented, producing timely results and ability to work both independently with minimal supervision and as a member of a scrum/product team.
- Track-record of successful project delivery, building collaborative cross-functional relationships, and an ability to find creative ways to solve business problems.
- Ability to balance the competing needs of multiple priorities and work in a dynamic environment; ability to perform under pressure and in stressful situations.
- Demonstrable capacity for learning technical concepts and adapting to new technologies quickly; ability to stay current with evolving best practices in data management.
- Familiar with healthcare provider data structures and sources; experienced with HIPAA regulations and methods for safeguarding PHI and PII through mitigation of data exposure risk.
- Knowledge of health care operations and structure, general requirements in an integrated delivery.
Benefits
- Yes
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