SEARCH CAREER OPPORTUNITIES

GENERAL SUMMARY OF POSITION: 

Under the general direction of the Associate Chief Information Officer or designee, the Sr Research Data Engineer is responsible for modeling complex clinical and research problems, discovering insights and identifying opportunities through the use of statistical, algorithmic, mining and visualization techniques. In addition to advanced analytic skills, this role is also proficient at integrating and preparing large, varied datasets, designing specialized database and computing environments, and presenting results. ETL Engineers work closely with clients, project/program managers, and other IT teams to turn data into actionable information and knowledge that can be used to make sound organizational decisions. Core traits include creative thinking, innovative proposals, and expert data mining techniques. They will need to validate their findings using an experimental and iterative approach.  In addition, he/she will perform diverse and complex duties in a manner consistent with a dynamic and active biomedical education and research community.

MAJOR RESPONSIBILITIES:

• Envision and deliver information systems solutions in alignment with the Medical School's strategic and tactical business plans.
• Identify efficient tools for business and clinical application design and development. Incorporate technology tools where appropriate
• Participate in the oral presentation of all project findings and abstracts including participation in periodic project status meetings and presentation of final project deliverables.
• Prepare informational/educational materials for users and train clinical researchers in the use of analytical datasets.
• Conduct advanced data analysis and complex design algorithms
• Work with IT teams to support data collection, integration, and retention requirements based on requirements.
• Make strategic recommendations on data collection, integration and retention requirements incorporating knowledge of best practices
• Develops innovative and effective approaches to solve analytical problems and communicate results and methodologies.
• Validate analysis using various modeling techniques.
• Identify/create appropriate algorithms to discover patterns in complex datasets.
• Partner with the data stewards to define data quality expectations.
• Develop usage and access control policies in collaboration with the data stewards
• Perform other duties as assigned.

REQUIRED QUALIFICATIONS:

• MS in Computer and/or Data Science, Informatics, a related field, or equivalent experience
• 5 years of experience in development and implementation of technologies preferably for an academic research organization.
• Experience working in a scientific research or academic environment
• Strong interpersonal and communication skills required.
• Demonstrated ability to provide documentation.
• Ability to communicate effectively in writing.

PREFERRED QUALIFICATIONS:

• 5+ years of experience in developing and supporting research informatics needs at a large healthcare academic center.
• 5+ Years of experience in production database support and information systems solutions implementation.
• 5+ experience building and consuming ETL/ELT services (e.g., SSIS, abt, Matillion, Talend, Informatica).
• Advanced experience with cloud technologies and services like AWS, Google Cloud, or Azure, along with their respective security levels and what tools the service providers make available through the cloud.
• Advance experience with B.I. tools (tableau, power BI, Qlik, Alteryx)
• Advanced skills in C#, MVC Development, WebAPI's, and microservices.
• Experience with JAVA, Python, Docker and Scala.
• Familiar with NoSQL databases (e.g., Hadoop, MongoDB) including associated tools such as key-value cache (Ignite, Coherence, Hazelcast), key-value store (Aerospike), Tuple store (Apache River), object database (pREST, ZopeDB), document store (BaseX, Clusterpoint, IBM Domino), wide column store (Amazon DynamoDB, Cassandra), native multi-model database (CosmosDB, MarkLogic), Apache Hive and Apache Spark,
• Familiarity with Cloud Data Warehouse (Snowflake, Azure Data Warehouse, Redshift).
• Familiarity with Machine Learning concepts and tools (HDInsight, Python, R).
• Familiarity with Epic Systems, especially their Clarity database and Epic Orchard.
• Familiarity with OMOP model and hospital ADT feeds.
• Familiarity with interoperability standards/protocols (FHIR, EDI, HL7, DICOM) and tools (Nextgen Connect, Iguana).
• Familiarity with public and private claims data set (SAFIP/OP, State IP/OP, BHI)

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