Data Analytics Engineer

Collects, transforms, and validates data from diverse sources, applying professional analytical techniques to ensure accuracy and reliability. Performs exploratory and descriptive analysis to identify trends, patterns, and key performance drivers for business stakeholders. Develops and maintains reports, dashboards, and visualizations that communicate analytical findings in a clear and actionable manner. Interprets data requirements, collaborates with business partners, and applies professional judgment to structure analyses that meet defined objectives. Documents analytical logic, data sources, and methodologies to support transparency, reproducibility, and continuous improvement. Supports cross-functional initiatives by providing data-driven insights and contributing to analytical problem-solving efforts. Identifies and recommends opportunities to streamline analytical workflows, standardize reporting, or enhance data quality. Builds proficiency in analytics tools, data modeling concepts, and best practices to expand analytical independence and effectiveness. Requirements Bachelor's degree in Data Analytics, Statistics, Mathematics, Computer Science, Information Systems, Business, or related discipline with 0-2 years of relevant experience. Demonstrated ability to collect, organize, and analyze data with attention to accuracy and detail. Experience preparing reports, dashboards, or visualizations using Excel or introductory business intelligence tools. Basic proficiency with SQL, Python, R, or comparable analytical tools. Strong critical thinking and problem-solving skills in a data-driven environment. Ability to communicate clearly with both technical and non-technical stakeholders. Interest in learning new data analysis techniques and technologies to support business insights. Demonstrated level of knowledge regarding applicable regulatory standards commensurate with the position's complexity and scope, contributing to organizational regulatory compliance. GMP quality management systems (e.g. ISO 13485) Clinical laboratory regulations (e.g. CAP, CLIA, NYSDOH, ISO 15189) Protected health information (e.g. HIPAA, GDPR) Operations within the regulated medical device environment (e.g. IVDD, IVDR, FDA 21 CFR 800 series, FDA 21 CFR Part 11) Development and Operations within a regulated clinical study environment (e.g. ICH E6 (GCP), ISO 20916, FDA 21 CFR Part 11, Part 50, Part 54, Part 56) Strong analytical and quantitative skills with the ability to interpret and communicate data findings clearly. Proficiency with Excel and exposure to analytical tools such as SQL, Python, R, or Power BI/Tableau. Basic understanding of data structures, relational databases, and data visualization principles. Core Competencies Demonstrates strong analytical and quantitative skills, with proficiency in data collection, organization, and analysis. Capable of developing reports and visualizations using tools like Excel, SQL, and Python while ensuring compliance with regulatory standards in a clinical or medical device environment. Highest-signal resume keywords Data Collection and Analysis Report and Dashboard Development SQL Proficiency Excel Proficiency Regulatory Compliance Knowledge ATS Optimization Keywords Hard Skills Data Analysis Data Validation Data Visualization SQL Python R Excel Analytical Techniques Data Modeling Quantitative Skills Soft Skills Critical Thinking Problem-Solving Clear Communication Industry Keywords GMP Quality Management Systems Clinical Laboratory Regulations Protected Health Information Regulated Medical Device Environment Clinical Study Environment Tools & Technologies Power BI Tableau Business Intelligence Tools #J-18808-Ljbffr