Senior Data Analyst Salary at Lifull Connect BETA

How much does a Lifull Connect Senior Data Analyst make?

As of March 2025, the average annual salary for a Senior Data Analyst at Lifull Connect is $83,647, which translates to approximately $40 per hour. Salaries for Senior Data Analyst at Lifull Connect typically range from $75,586 to $90,791, reflecting the diverse roles within the company.

It's essential to understand that salaries can vary significantly based on factors such as geographic location, departmental budget, and individual qualifications. Key determinants include years of experience, specific skill sets, educational background, and relevant certifications. For a more tailored salary estimate, consider these variables when evaluating compensation for this role.

DISCLAIMER: The salary range presented here is an estimation that has been derived from our proprietary algorithm. It should be noted that this range does not originate from the company's factual payroll records or survey data.

Lifull Connect Overview

Website:
lifullconnect.com
Size:
<25 Employees
Revenue:
$5M - $10M
Industry:
Software & Networking

LIFULL Connect is the leading digital marketplaces group owned by LIFULL. It serves over 180 million users monthly, with more than 250 sites in 63 countries. LIFULL Connect seeks to connect people and help them make some of the biggest decisions in their life and its mission is to change people's lives, one search at a time. LIFULL CONNECT has offices in Europe, Southeast Asia, and Latin America, including Bogota, Lima, and Santiago de Chile. Trovit, Mitula, Nestoria, and Dot Property are some of the real estate-focused websites in its portfolio.

See similar companies related to Lifull Connect

What Skills Does a person Need at Lifull Connect?

At Lifull Connect, specify the abilities and skills that a person needs in order to carry out the specified job duties. Each competency has five to ten behavioral assertions that can be observed, each with a corresponding performance level (from one to five) that is required for a particular job.

  1. Analysis: Analysis is the process of considering something carefully or using statistical methods in order to understand it or explain it.
  2. SQL: Structured Query Language) is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or for stream processing in a relational data stream management system (RDSMS).
  3. Insight: Insight is the understanding cause and effect based on the identification of relationships and behaviors within a model, context, or scenario.
  4. Data Analysis: Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively. Data mining is a particular data analysis technique that focuses on modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. In statistical applications, data analysis can be divided into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA). EDA focuses on discovering new features in the data while CDA focuses on confirming or falsifying existing hypotheses. Predictive analytics focuses on application of statistical models for predictive forecasting or classification, while text analytics applies statistical, linguistic, and structural techniques to extract and classify information from textual sources, a species of unstructured data. All of the above are varieties of data analysis.
  5. Tableau: Using business intelligence software to perform data analysis, data visualization, and the BI process of an organization.

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Check more jobs information at Lifull Connect

Job Title Average Lifull Connect Salary Hourly Rate
2 Accounting Assistant $40,117 $19
3 Chief Accounting Officer $195,688 $94
4 Chief Technology Officer $244,727 $118
5 Head of Customer Success $178,445 $86
6 Performance Marketing Specialist $62,860 $30
7 Quality Assurance Lead $114,401 $55
8 Sales Executive $203,120 $98
9 Senior Developer $90,886 $44
10 Software Architect $119,517 $57
11 Backend Engineer $98,170 $47
12 Big Data Engineer $118,111 $57
13 Data Analytics Lead $92,664 $45

Hourly Pay at Lifull Connect

The average hourly pay at Lifull Connect for a Senior Data Analyst is $40 per hour. The location, department, and job description all have an impact on the typical compensation for Lifull Connect positions. The pay range and total remuneration for the job title are shown in the table below. Lifull Connect may pay a varying wage for a given position based on experience, talents, and education.
How accurate does $83,647 look to you?

FAQ about Salary and Jobs at Lifull Connect

1. How much does Lifull Connect pay per hour?
The average hourly pay is $40. The salary for each employee depends on several factors, including the level of experience, work performance, certifications and skills.
2. What is the highest salary at Lifull Connect?
According to the data, the highest approximate salary is about $90,791 per year. Salaries are usually determined by comparing other employees’ salaries in similar positions in the same region and industry.
3. What is the lowest pay at Lifull Connect?
According to the data, the lowest estimated salary is about $75,586 per year. Pay levels are mainly influenced by market forces, supply and demand, and social structures.
4. What steps can an employee take to increase their salary?
There are various ways to increase the wage. Level of education: An employee may receive a higher salary and get a promotion if they obtain advanced degrees. Experience in management: an employee with supervisory experience can increase the likelihood to earn more.