Ent. App Developer/Sr. – CIBMTR Data Engineer
Prepare data for analytical and operational uses to support diverse stakeholder needs throughout the CIBMTR, including—statisticians and data scientists, scientific directors and third-party partners. Design, develop and implement data-centric solutions aligned to the user needs, aware of diverse data structures and supporting data quality, efficiency and reliability.
- Collaborate with data subject matter experts and technical professionals in mid to large size multidisciplinary projects as a lead, or as a key member of scrum team in support of data centric solutions.
Work alongside subject matter experts to acquire deep understanding of data domains and data use to support user data analysis needs
Work with architects to design, build, test, implement and maintain architectures within a data ecosystem (relational databases, marts, lakes) that organizes and structures data for analytical or operational uses.
Design, build, test, implement and maintain ETL, data pipelines and components that ingest, integrate, and aggregate data from disparate sources, domains and data models, including—relational databases, data warehouse, data mart and data lake. Design, build, test and maintain data set processes, including stored procedures, automated quality validation checks, and access and security components
Works as part of a team to develop APIs.
Design & build data set processes, including orchestrating workloads, automating processes and validating data quality checks
Conduct data profiling and recommend ways to improve data quality, reliability, and efficiency
- Optimize and retrieve data sets to promote high availability of self-service access to data
Prepare and maintain system documentation for your work that aligns with internal SOP’s, best practice and regulatory compliance.
- Perform other duties as required
Knowledge – Skills – Abilities
Knowledge of computers, electronics, digital media, databases, applications, software development, risk management, and information security. The candidate will have the following qualifications:
Strong data profiling skills along with uncompromising commitment to preserve data quality and integrity
Strong knowledge of data modeling as well as centralized and decentralized data warehousing principles
Highly proficient with SQL
Knowledge of AGILE Scrum
Basic knowledge of advanced analytical methods, including machine learning preferred
Support, systems analysis, troubleshooting, problem solving, and listening skills.
Proficient with PL/SQL and or SQL
Knowledge of data interoperability and data transfer standards
Knowledge of R or SAS is preferred
Knowledge of scripting languages:
Knowledge of one or more of C#, .NET and Java is preferred
Knowledge of RESTful web services or APIs preferred.
Appropriate experience may be substituted on equivalent basis
Minimum Required Education:
Minimum Required Experience:
Computer Science, Informatics, other technical discipline in healthcare or life science
Diversity and Inclusion
The Medical College of Wisconsin defines diversity as a commitment to recognizing and appreciating the variety of individual differences in an environment that promotes and celebrates individual and collective achievement. The diversity of MCW continues to be an important source of innovative ideas and creative accomplishments.
MCW as an Equal Opportunity Employer and Commitment to Non-Discrimination
The Medical College of Wisconsin (MCW) is an Equal Opportunity Employer. We are committed to fostering a diverse community of outstanding faculty, staff, and students, as well as ensuring equal educational opportunity, employment, and access to services, programs, and activities, without regard to an individual's race, color, national origin, religion, age, disability, sex, gender identity/expression, sexual orientation, marital status, pregnancy, predisposing genetic characteristic, or military status. Employees, students, applicants or other members of the MCW community (including but not limited to vendors, visitors, and guests) may not be subjected to harassment that is prohibited by law or treated adversely or retaliated against based upon a protected characteristic.