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Data Analyst Jobs in Jupiter, FL (NOW HIRING)

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Data Analyst information

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$33.2K

$80.8K

$133K

How much do data analyst jobs pay per year?

As of Sep 5, 2026, the average yearly pay for data analyst in Jupiter, FL is $80,808.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,100.00 and $94,800.00 per year, depending on experience, location, and employer.

What does a data analyst do?

A Data Analyst is responsible for collecting, processing, and analyzing data to help organizations make informed business decisions. They use statistical tools and software to interpret data sets, identify trends, and create visual reports. Data Analysts often collaborate with other departments to provide actionable insights and support strategic planning. Their work helps organizations optimize operations, track performance, and solve business problems using data-driven approaches.

What are the key skills and qualifications needed to thrive as a data analyst, and why are they important?

To thrive as a Data Analyst, you need strong analytical skills, proficiency in statistics, and a relevant degree such as in mathematics, statistics, or computer science. Familiarity with data analysis tools like SQL, Excel, Python or R, and experience with visualization platforms such as Tableau or Power BI are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help analysts interpret data insights and present findings clearly to stakeholders. These skills are crucial for transforming raw data into actionable business insights that drive informed decision-making.

What are some common challenges data analysts face when working with large datasets, and how are they typically addressed?

Data Analysts often encounter challenges such as data quality issues, missing or inconsistent values, and slow processing times when handling large datasets. These challenges are typically addressed by implementing data cleaning routines, using advanced data management tools, and leveraging programming languages like Python or R for efficient data manipulation. Collaboration with database administrators and IT teams is also common to ensure data integrity and optimize data storage solutions. Staying updated with best practices in data wrangling and visualization helps Data Analysts deliver accurate and actionable insights.

What is the difference between Data Analyst vs Data Scientist?

AspectData AnalystData Scientist
Required CredentialsBachelor's degree in statistics, mathematics, or related field; often certifications in data analysis toolsBachelor's or master's in computer science, statistics, or related; often advanced certifications or degrees
Work EnvironmentBusiness settings, focusing on data reporting and visualizationResearch and development environments, focusing on predictive modeling and complex algorithms
Employer & Industry UsageRetail, finance, healthcare, and marketing companiesTech firms, research institutions, and large enterprises

While both roles analyze data, Data Analysts primarily focus on interpreting existing data to generate reports and insights, whereas Data Scientists develop predictive models and advanced algorithms to forecast trends and solve complex problems.

Do data analysts get paid well?

Data analysts typically earn competitive salaries that vary by experience, location, and industry. Entry-level positions may start lower, but with skills in tools like Excel, SQL, and data visualization, salaries tend to increase with expertise and certifications. Overall, data analysis is considered a well-paying field with growth potential.

Is it hard to get a data analyst job?

Securing a data analyst position can be competitive, as it often requires strong skills in data manipulation, statistical analysis, and proficiency with tools like Excel, SQL, or Python. Candidates with relevant education, certifications, and experience tend to have better chances, but persistence and continuous skill development are important.

What work does a data analyst do?

A data analyst collects, processes, and analyzes large datasets to identify trends, patterns, and insights that support business decision-making. They use tools like Excel, SQL, and data visualization software to interpret data and communicate findings to stakeholders. Strong analytical skills and attention to detail are essential for this role.
More about Data Analyst jobs

What are the most commonly searched types of Data Analyst jobs in Jupiter, FL?

The most popular types of Data Analyst jobs in Jupiter, FL are:

What are popular job titles related to Data Analyst jobs in Jupiter, FL?

For Data Analyst jobs in Jupiter, FL, the most frequently searched job titles are:

What job categories do people searching Data Analyst jobs in Jupiter, FL look for?

The top searched job categories for Data Analyst jobs in Jupiter, FL are:

What cities near Jupiter, FL are hiring for Data Analyst jobs?

Cities near Jupiter, FL with the most Data Analyst job openings:

Data Analyst jobs near you
Infographic showing various Data Analyst job openings in Jupiter, FL as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 17% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $80,808 per year, or $38.9 per hour.

Database Analyst

Delan Associates, Inc.

Palm Beach Gardens, FL • On-site

Contractor

Re-posted 17 hours ago

Job description

Database Analyst / Data Quality & Requirements Specialist (SQL + Excel)
We're looking for a database-focused analyst with strong SQL (PostgreSQL) skills and a sharp eye for detail. This person is naturally curious, asks "why?" before "how?", and isn't afraid to challenge assumptions to protect data integrity and improve processes. You'll manage, update, and audit databases, partner with stakeholders to gather requirements, and help ensure our data is accurate, reliable, and usable.
This is a great fit for someone who blends hands-on database skills with a business analyst mindset-someone who can independently clarify needs, translate them into data logic, and validate results end-to-end.
Key Responsibilities
• Maintain, update, and audit relational databases (PostgreSQL), ensuring accuracy, consistency, and traceability.
• Write and optimize SQL queries, including multi-table joins, aggregations, and validation checks.
• Perform data quality checks, reconcile discrepancies, and document root causes and fixes.
• Build and maintain Excel-based audit tools (pivots, lookups, Power Query as applicable) for reporting and verification.
• Partner with internal users to gather requirements, challenge unclear requests, and translate business needs into data definitions and logic.
• Create and maintain documentation: table definitions, field mappings, audit results, and change logs.
• Support process improvements and controls around data updates, permissions, and governance.
Required Qualifications
• Strong SQL experience, including PostgreSQL (or equivalent with ability to ramp quickly).
• Solid understanding of relational database fundamentals (keys, constraints, normalization concepts, data integrity).
• Demonstrated experience managing, updating, and auditing datasets/databases.
• Advanced Excel skills (filters, pivot tables, XLOOKUP/VLOOKUP, data validation; Power Query is a plus).
• Demonstrated experience performing data audits and documenting findings, remediation steps, and outcomes (repeatable + traceable work).
• Comfortable owning ambiguous requests and independently questioning stakeholders to gather requirements and confirms data definitions before building.
• Can explain logic and assumptions clearly to both technical and non-technical stakeholders.
• Shows critical thinking, asks "why," identifies risks and edge cases, and proposes better approaches rather than executing blindly.
• Proven ability to investigate inconsistencies, ask probing questions, and validate assumptions.
• Strong written and verbal communication; comfortable working directly with stakeholders.
Nice-to-Have Qualifications
• Mechanical or engineering background/familiarity (or experience supporting engineering/asset-heavy environments).
• Familiarity with AVEVA PI (PI System / PI Data Archive / PI Vision) or time-series data concepts.
• Familiarity with IBM Maximo (asset management / work orders / equipment hierarchies).
• Familiarity with AWS (RDS, S3, Athena/Glue, IAM concepts, basic cloud data patterns).
• Experience acting as a BA: independently gathering requirements, defining acceptance criteria, mapping data sources to outputs.
• Familiarity with tools like Quest (e.g., Toad) or data access/auditing tools.

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