Encounter Data Management Professional Salary in 2024

Salary details

The average Encounter Data Management Professional salary lies between USD 57,700 and USD 79,500 globally. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Dec. 15, 2024

Top 20 Job Tags for Encounter Data Management Professional roles

The three most common job tag items assiciated with Encounter Data Management Professional job listings are Data management, Excel and SQL. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

Data management | 19 jobs Excel | 18 jobs SQL | 15 jobs Research | 8 jobs SAS | 8 jobs Data analysis | 7 jobs Finance | 5 jobs Security | 5 jobs Oracle | 3 jobs Power BI | 3 jobs Databricks | 2 jobs Python | 1 jobs Testing | 1 jobs Bigtable | 1 jobs

Top 20 Job Perks/Benefits for Encounter Data Management Professional roles

The three most common job benefits and perks assiciated with Encounter Data Management Professional job listings are Insurance, Parental leave and Health care. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Insurance | 19 jobs Parental leave | 18 jobs Health care | 18 jobs Competitive pay | 18 jobs Medical leave | 18 jobs Salary bonus | 14 jobs Wellness | 9 jobs Flex hours | 6 jobs Career development | 4 jobs 401(k) matching | 2 jobs Startup environment | 2 jobs Team events | 2 jobs Flex vacation | 1 jobs Gear | 1 jobs

Salary Composition for Encounter Data Management Professionals

The salary for an Encounter Data Management Professional typically comprises a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or benefits. The composition can vary significantly based on region, industry, and company size. In regions with a high cost of living, such as major metropolitan areas in the United States, the base salary might be higher to compensate for living expenses. In contrast, companies in smaller markets might offer lower base salaries but compensate with more substantial bonuses or benefits.

In industries like healthcare or finance, where data management is critical, bonuses might be more performance-driven, reflecting the impact of data accuracy and management on the company's bottom line. Larger companies often provide more comprehensive benefits packages, including health insurance, retirement plans, and stock options, which can significantly enhance the overall compensation package.

Steps to Increase Salary from This Position

To increase your salary from the position of an Encounter Data Management Professional, consider the following strategies:

• Skill Enhancement: Continuously update your skills in data analysis, machine learning, and data management tools. Proficiency in advanced analytics and AI can make you more valuable to employers.
• Advanced Education: Pursuing a master's degree or specialized certifications in data science or AI can open up higher-paying opportunities.
• Networking: Engage with professional networks and industry groups to learn about new opportunities and trends. Networking can also lead to mentorship and career advancement opportunities.
• Leadership Roles: Aim for leadership or managerial roles within your organization. These positions often come with higher salaries and additional responsibilities.
• Industry Transition: Consider transitioning to industries that pay higher salaries for data management roles, such as tech or finance.

Educational Requirements

Most Encounter Data Management Professional roles require at least a bachelor's degree in a relevant field such as computer science, information technology, data science, or a related discipline. A strong foundation in mathematics, statistics, and computer programming is often essential. Some positions may prefer candidates with a master's degree, especially for roles that involve more complex data analysis or management responsibilities.

Helpful Certifications

Certifications can enhance your qualifications and demonstrate your expertise to potential employers. Some valuable certifications include:

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• Microsoft Certified: Azure Data Scientist Associate: Demonstrates your skills in using Azure's machine learning tools.
• Google Professional Data Engineer: Focuses on designing, building, and operationalizing data processing systems.
• SAS Certified Data Scientist: Covers data manipulation, predictive modeling, and machine learning.

Experience Requirements

Typically, employers look for candidates with at least 2-5 years of experience in data management, data analysis, or a related field. Experience with specific data management tools and software, such as SQL, Python, R, or data visualization tools, is often required. Experience in the specific industry, such as healthcare or finance, can also be advantageous.

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