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Data Analytics Professional Jobs (NOW HIRING)

Cotality

Data Analytics

Dallas, TX · On-site

$113K - $136K/yr

Data Analysis & Insights: Perform deep-dive statistical analysis using SQL, Python, or R to ... We offer an empowered work environment that encourages creativity, initiative and professional ...

Palnar

Data Analytics

Reston, VA · On-site

... professional) setting. - Good to have hands-on development experience with Hadoop and the Hadoop ... Data Analyst teams to develop and implement the Ab Initio solution - Develop generic solutions ...

YourCode

Data Analytics Architect

Little Rock, AR · On-site

Bachelor's degree in Computer Science, Engineering, or related field/equivalent professional experience; * Minimum of 5 years of hands-on experience in data engineering, analytics, or data platform ...

FutureSoft Consulting Inc.

Data Analyst

Harrisburg, PA · On-site

This role is ideal for a business-facing analytics professional with strong experience in data analysis, dashboard development, reporting, visualization, stakeholder communication, and data-driven ...

Glenmont Group

Data Analytics Developer

Manhattan, NY · On-site

$145 - $155K/hr

The Data Analytics Developer is responsible for developing analytical data structures, data ... Bachelor's degree required; professional certifications are a plus. * The ideal candidate should ...

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How much do data analytics professional jobs pay per hour?

As of Jun 29, 2026, the average hourly pay for data analytics professional in the United States is $54.75, according to ZipRecruiter salary data. Most workers in this role earn between $43.99 and $62.02 per hour, depending on experience, location, and employer.

What is the highest paying job in data analytics?

The highest paying roles in data analytics are often senior positions such as Data Analytics Director, Chief Data Officer, or Data Science Manager, which require extensive experience, advanced skills in programming, machine learning, and data strategy. These roles typically offer six-figure salaries and may include leadership responsibilities and specialized certifications.

What do data analytics professionals do?

Data analytics professionals analyze large datasets to identify trends, patterns, and insights that support business decision-making. They use tools like Excel, SQL, and data visualization software, and often work with stakeholders to interpret data and recommend actions. Strong analytical skills and knowledge of statistical methods are essential in this role.

What is the difference between Data Analytics Professional vs Data Analyst?

AspectData Analytics ProfessionalData Analyst
CredentialsOften requires a degree in data science, statistics, or related fields; certifications like CAP, Google Data AnalyticsTypically holds a degree in similar fields; certifications are common but not mandatory
Work EnvironmentWorks across various industries, often in teams, handling complex data projectsFocuses on data collection, cleaning, and basic analysis, often in business settings
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firmsCommon in retail, marketing, finance, and healthcare sectors

While both roles involve analyzing data, Data Analytics Professionals often handle more complex projects and require broader skill sets, including advanced analytics and data modeling. Data Analysts typically focus on data preparation and basic analysis to support decision-making. Both roles are essential in data-driven organizations, but the scope and complexity of tasks differ.

Is AI replacing data analysts?

AI tools are automating certain data analysis tasks, but the role of a data analytics professional involves interpreting complex data, developing insights, and making strategic recommendations that AI cannot fully replicate. Data analysts with skills in programming, statistical methods, and data visualization remain essential for translating data into actionable business decisions.

Is 40 too late for data science?

Data analytics professionals can successfully transition into data science at any age, including 40, as the field values skills such as programming, statistical analysis, and domain knowledge. Many individuals acquire relevant certifications or learn tools like Python, R, and SQL later in their careers to enhance their qualifications.
What cities are hiring for Data Analytics Professional jobs? Cities with the most Data Analytics Professional job openings:
What are the most commonly searched types of Data Analytics jobs? The most popular types of Data Analytics jobs are:
What states have the most Data Analytics Professional jobs? States with the most job openings for Data Analytics Professional jobs include:
Data Analytics Professional jobs near you

Data Analytics Developer

FMNE Insurance Company

Lincoln, NE • On-site

Other

Medical, Retirement

Posted 18 days ago

Key responsibilities

  • Extract, transform, and load data to support actuarial analysis.

  • Design, develop and maintain dashboards, reports, and visualizations for stakeholders.

  • Collaborate with the actuarial team to understand data requirements and provide accurate, timely data for actuarial functions.

Job description

FMNE Insurance is seeking a Data Analytics Developer in our Actuarial Department. We're looking for a highly analytical and solutions-oriented data professional who is passionate about transforming complex data into meaningful insights that support actuarial and business decision-making. The ideal candidate is collaborative, technically strong, and detail-focused, with the ability to manage multiple priorities, build trusted relationships across teams, and develop efficient, reliable data solutions. Join a stable, values-driven company with deep Midwest roots and a strong team-focused culture.
This position is not eligible for visa sponsorship. Applicants must be authorized to work in the United States on a full-time basis. Please submit a resume and cover letter for consideration.
We offer a competitive salary and a comprehensive benefits package, including health coverage, a generous 401(k), pension plan, wellness programs and a hybrid work model for eligible employees.
Role Overview of a Data Analytics Developer
The Data Analytics Developer is a critical member of the Actuarial team and is responsible for, but not limited to, the preparation, transformation, and integration of data for accurate and effective actuarial analyses. This role collaborates closely with Data Scientists, Actuarial Analysts, and other stakeholders to ensure data quality, reliability, and performance of solutions.
Responsibilities of a Data Analytics Developer

  • Demonstrates the Company's mission, while successfully performing its core values related to integrity, service, excellence, stability, strength, respect, and teamwork.
  • Responsible for extracting, transforming, and loading (ETL/ELT) data to support actuarial analysis.
  • Perform data cleansing, transformation, and validation processes for data integrity and accuracy.
  • Create tables, views and stored procedures to support Actuarial processes.
  • Collaborate with the actuarial team to understand data requirements and provide accurate, timely data for pricing, reserving, and other actuarial functions.
  • Design, develop and maintain dashboards, reports and visualizations that empower stakeholders to make data-informed decisions and drive business outcomes.
  • Work in conjunction with the IT department to maintain up-to-date and optimized actuarial infrastructure.
  • Understand and work with colleagues to ensure continued compliance with data governance standards and security policies.
  • Maintain ETL processes, reports and dashboards.
  • Work closely with other departments to understand business needs.
  • Build and maintain trust with key stakeholders.
  • Regular and timely attendance in the office is an essential function of the position.
Skills and Qualifications of a Data Analytics Developer
  • Bachelor's degree in MIS, Computer Science, or other analytical areas.
  • Minimum of three years of experience working with data.
  • Must possess strong SQL skills.
  • Knowledge of SQL Server, SSIS, SSRS, Power BI or equivalent.
  • Experience with Python and/or R.
  • Familiar with Azure data services including Azure Data Factory (ADF).
  • Strong ability and desire to use technology to solve complex problems.
  • Knowledge of data tools, techniques, and manipulation including cloud platforms, programming languages, and technology platforms.
  • Knowledge of insurance industry preferred.
  • Aptitude for solving complex problems and overcoming challenges, demonstrating resilience and adaptability in finding solutions.
  • Demonstrated success in addressing business needs with analytics.
  • Ability to manage multiple tasks at the same time in a dynamic environment.
  • Excellent oral and written communication skills, self-driven, and strong quantitative, analytical, and interpersonal skills.

FMNE Insurance Company recognizes that an individual with a disability may require accommodation to enable them to successfully perform a job function. Should you require such accommodation, please indicate the job function and suggested accommodation during the interview process. FMNE will attempt to make reasonable accommodation.

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