Data Engineer

Position Summary: We are seeking a skilled Data Engineer (mid-level) to join our team. The ideal candidate will be responsible for conducting various analytical activities, developing and managing databases, and leveraging advanced tools to support our data science initiatives. This role requires strong technical expertise, problem-solving skills, and the ability to collaborate with cross-functional teams to provide optimal data solutions.

Key Responsibilities:

• Conduct analytical activities including collecting, aggregating, organizing, validating, cleaning, analyzing, interpreting, processing, and reporting on qualitative and quantitative data sets.
• Collaborate with the Client to assess and define problems, determine analytics needed, and provide optimal solutions.
• Apply quantitative and qualitative statistical methods and models to describe, analyze, synthesize, and interpret datasets
• Collect, code, recode, and clean data for analyses of clinical research, investment, and expenditure activities.
• Create new datasets from multiple sources and large databases by selecting and joining appropriate tables and variables.
• Plan, design, develop, and manage organizational databases to ensure efficient data storage, access, and security.
• Write queries, stored procedures, and functions for database development.
• Monitor databases' performance, scalability, and security, and modify procedures to optimize database designs.
• Apply machine learning, NLP, and other analytic tools to derive knowledge from extramural grant and administrative datasets.
• Develop data visualizations using tools like Qlik, PowerBI, and RShiny to present data to a wide audience.
• Produce data reports to support NIH and OER policy initiatives in response to stakeholder requests.
• Monitor and verify data quality, identify deficiencies, errors, and anomalies, and recommend corrective actions.
• Identify areas for improvement in existing tools and recommend solutions to increase efficiency or optimize results.
• Document and centrally store code following industry standards and information security procedures.
• Provide technical presentations, demonstrations, and training sessions on data analyses and findings to non-experts and leadership.

Qualifications:

• Bachelor’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, Business Analytics or related quantitative disciplines field.
• 3-5 years of experience in data engineering, data analysis, or a related field.
• Proficiency in programming languages such as R, Python, SQL, NoSQL, and others.
• Experience with statistical computing packages like R, SAS, SPSS, MATLAB, and STATA.
• Strong analytical, problem-solving, and data visualization skills.
• Excellent communication and presentation skills.
• Ability to collaborate effectively with cross-functional teams and stakeholders.