Senior Tableau Data Visualization Engineer - Health and Life Sciences

Key Skills

Agile methodologies, Analytical Techniques, CDC, Data Analysis, Data Modeling, Data science techniques, Data Visualization, Design, Effective communication skills, English Proficiency, ETL frameworks, Flight Data Monitoring-FDM, Health and Safety, Leadership Skill, Management, Mentoring, MS Dynamics, Programming, Python Programming, Software Development, SQL, Statistics, Tableau

Job Description

Leidos is actively searching for a Senior Tableau Data Visualization Engineer with certification to support our federal customer, NIH ARPA-H. This pivotal role is dedicated to addressing complex data analysis requirements within the health and life sciences domain.

This is a hybrid role with customer site in DC Metro required 2 to 3 days a week.

Key Responsibilities:

• Design, develop, and manage sophisticated Tableau dashboards and reports.
• Lead complex data analysis projects and provide expert insights.
• Collaborate closely with research scientists to understand and visualize complex scientific data.
• Facilitate effective communication of data insights to scientific and non-technical audiences.
• Collaborate with cross-functional teams to ensure data accuracy and effectiveness of visualizations.
• Manage data lineage and record linkage processes within visualization projects.
• Implement data obfuscation techniques to maintain data privacy.
• Mentor junior staff and lead team initiatives.

Qualifications:

• Bachelor's degree in a relevant field such as Computer Science, IT, Data Science, Statistics, or a related discipline. Master’s degree preferred.
• Tableau Certification (Tableau Desktop Certified Professional or similar) is required.
• Minimum of 8 years of experience in Tableau data visualization with a focus on complex data analysis.
• Proven experience in the health and life sciences domain; prior work with NIH, FDA, or CDC is highly preferred.
• Exceptional analytical, problem-solving, and communication skills.
• Ability to obtain a public trust clearance.
• Familiarity with the specific data challenges and requirements within the health and life sciences domain. Understanding of healthcare data standards, regulations, and privacy concerns is crucial.

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Preferred Skills:

• Advanced knowledge of data modeling, ETL processes, and additional data visualization tools.
• Strong leadership and team management skills.
• Proficiency in additional data visualization tools and data science methodologies.
• Leadership and team management experience.
• Given the dynamic nature of technology and data in the health and life sciences sector, a willingness to stay updated on the latest industry trends, tools, and best practices is crucial
• Knowledge of programming languages like Python or SQL

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Pay Range:

Pay Range $81,250.00 - $146,875.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

About Leidos

Leidos is a Fortune 500® technology, engineering, and science solutions and services leader working to solve the world’s toughest challenges in the defense, intelligence, civil, and health markets. The company’s 47,000 employees support vital missions for government and commercial customers. Headquartered in Reston, Virginia, Leidos reported annual revenues of approximately $14.4 billion for the fiscal year ended December 30, 2022. For more information, visit www.Leidos.com.

Pay and Benefits

Pay and benefits are fundamental to any career decision. That's why we craft compensation packages that reflect the importance of the work we do for our customers. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available here.

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