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Remote Data Analyst Jobs in High Ridge, MO (NOW HIRING)

nimble

Data Engineer

Chesterfield, MO · On-site +1

$113K - $136K/yr

Description Data Engineer Chesterfield Office Hybrid or Remote Why You'll Want to Join! Join a ... Your ETL/ELT pipelines enable our analytics and data science teams to unlock the full potential of ...

Nimble Solutions

Data Engineer

Chesterfield, MO · On-site +1

$113K - $136K/yr

Job Type Full-time Description Data Engineer Chesterfield Office Hybrid or Remote Why You'll Want ... Your ETL/ELT pipelines enable our analytics and data science teams to unlock the full potential of ...

Koantek

Data Engineer - Multiple Positions

Chesterfield, MO · Remote

$113K - $136K/yr

United States - Remote Employment Type: Full-Time and Contract Data Engineer Description: As a Data Engineer at Koantek, you will leverage advanced data engineering techniques and analytics to ...

Wood Plc

GIS Analyst - FEMA

Ballwin, MO · Remote

Perform GIS database development, qualitative/quantitative analysis, and mapping as a member of a ... programs for data collection, engineering, and environmental applications #LI-Remote Skills ...

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All JobsData Analyst JobsRemote Data Analyst JobsRemote Data Analyst Jobs in High Ridge, MO

Remote Data Analyst information

See High Ridge, MO salary details

$31K

$75.5K

$124.2K

How much do remote data analyst jobs pay per year?

As of Jul 10, 2026, the average yearly pay for remote data analyst in High Ridge, MO is $75,463.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,100.00 and $88,600.00 per year, depending on experience, location, and employer.

Is there a high demand for data analysts?

The demand for data analysts remains strong across various industries due to the increasing reliance on data-driven decision making. Organizations seek professionals skilled in data visualization, statistical analysis, and tools like Excel, SQL, and Python, leading to steady job growth in this field.

What are the key skills and qualifications needed to thrive as a Remote Data Analyst, and why are they important?

To thrive as a Remote Data Analyst, you need strong analytical skills, proficiency in statistics, and a degree in a quantitative field such as mathematics, statistics, or computer science. Familiarity with data analysis tools like SQL, Excel, Python or R, and visualization platforms such as Tableau or Power BI is typically required. Excellent communication, self-motivation, and time management are crucial soft skills for collaborating remotely and presenting insights effectively. These skills ensure accurate data-driven decision-making and effective remote teamwork in a digital work environment.

Can I do a data analyst job remotely?

Yes, many data analyst positions are available for remote work, especially those that involve analyzing data, creating reports, and using tools like Excel, SQL, and data visualization software. Remote data analysts typically need strong communication skills and proficiency with relevant software to collaborate effectively with teams online.

Is 40 too late for data science?

For a remote data analyst role, age is generally not a barrier; many professionals transition into data science or analytics later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and tools like SQL or Python, regardless of age. Continuous learning and building a strong portfolio can help late entrants compete effectively in the field.

How do Remote Data Analysts typically collaborate with team members and stakeholders given the virtual work environment?

Remote Data Analysts often rely on digital communication tools such as Slack, Microsoft Teams, and Zoom to stay connected with colleagues and stakeholders. They participate in regular virtual meetings, share dashboards or reports via cloud-based platforms, and provide data-driven insights to support decision-making. Successful remote analysts proactively communicate their findings, clarify requirements, and coordinate with cross-functional teams such as IT, marketing, or finance to ensure alignment on project goals and deliverables.

What does a Remote Data Analyst do?

A Remote Data Analyst is responsible for collecting, processing, and analyzing data to help organizations make informed business decisions, all while working from a location outside of a traditional office. They use statistical tools and software to interpret complex datasets, identify trends, and generate reports. Remote Data Analysts collaborate with team members via digital communication platforms and often present their findings to stakeholders to guide strategy and operations. Their work is essential in industries such as finance, healthcare, marketing, and technology, where data-driven decisions are crucial.

What is the difference between Remote Data Analyst vs Remote Data Scientist?

AspectRemote Data AnalystRemote Data Scientist
Required CredentialsBachelor's in Data, Statistics, or related field; often certifications in Excel, SQL, or TableauBachelor's or Master's in Data Science, Computer Science, or related; certifications in Python, R, machine learning
Work EnvironmentPrimarily office-based or remote, focusing on data analysis and reportingPrimarily remote, involving complex data modeling and predictive analytics
Employer & Industry UsageUsed across finance, marketing, healthcare, and retail sectorsCommon in tech, finance, and research industries

Remote Data Analysts focus on interpreting data, creating reports, and supporting decision-making, while Remote Data Scientists develop models, perform advanced analytics, and work on predictive insights. Both roles require strong analytical skills, but Data Scientists typically have more technical expertise in programming and machine learning.

Will AI replace data analyst?

AI tools can automate routine data processing and analysis tasks, but the role of a data analyst involves interpreting insights, understanding context, and communicating findings, which currently require human judgment. Data analysts will likely evolve to work alongside AI, focusing more on complex analysis, strategy, and decision-making that AI cannot fully replicate.

What Does a Remote Data Analyst Do?

Remote data analysts use a range of methods to chart, examine, and analyze data for their clients. Unlike in-house data analysts, remote data analysts, work from home or a different location outside of the office. As a remote data analyst, your job is to evaluate a company’s data using a combination of mathematical inspection, transformation, and modeling techniques to simplify and condense it. Once the analysis is complete, you create reports for management to use to make critical decisions; this is why remote data analysts need to confirm the accuracy of the data. You may also need to present your reports to stakeholders.

More about Remote Data Analyst jobs
What are the most commonly searched types of Data Analyst jobs in High Ridge, MO? The most popular types of Data Analyst jobs in High Ridge, MO are:
What job categories do people searching Remote Data Analyst jobs in High Ridge, MO look for? The top searched job categories for Remote Data Analyst jobs in High Ridge, MO are:
What cities near High Ridge, MO are hiring for Remote Data Analyst jobs? Cities near High Ridge, MO with the most Remote Data Analyst job openings:
Remote Data Analyst jobs near you
Infographic showing various Remote Data Analyst job openings in High Ridge, MO as of July 2026, with employment types broken down into 5% Internship, 85% Full Time, 5% Temporary, and 5% Contract. Highlights an 100% Remote job distribution, with an average salary of $75,463 per year, or $36.3 per hour.
Data Engineer

Data Engineer

nimble

Chesterfield, MO • On-site, Remote

$113K - $136K/yr

Other

Re-posted 16 days ago

Job description

Description


Data Engineer

Chesterfield Office Hybrid or Remote


Why You'll Want to Join! 


Join a leading Revenue Cycle Management (RCM) company dedicated to transforming healthcare data into actionable insights. We leverage cutting-edge technology to streamline financial and operational processes, improving efficiency and patient outcomes. We are looking for a Data Engineer to help optimize data pipelines and build a next-generation data infrastructure incorporating technologies such as Microsoft Fabric, Azure Synapse, Databricks, and Snowflake.


Position Overview


Lead the modernization of our data infrastructure as a Data Engineer for nimble. You'll architect scalable cloud-native pipelines using Microsoft Fabric and Databricks to transform healthcare data-claims, EMR/EHR, HL7/FHIR-into actionable insights that drive revenue cycle optimization and clinical outcomes.


Why This Role Matters


Healthcare data engineering is mission-critical: clean, governed data flows directly impact financial accuracy, compliance, and the decisions that improve patient care. Your ETL/ELT pipelines enable our analytics and data science teams to unlock the full potential of healthcare data.


Key Responsibilities


Design, build, and optimize ETL/ELT pipelines using Azure Synapse, Databricks, and Snowflake

Develop robust data models and schemas for healthcare datasets, including claims, EMR/EHR, HL7, and FHIR standards

Write and optimize SQL queries for performance across large healthcare datasets

Implement data governance, quality frameworks, and HIPAA compliance controls

Collaborate with analytics, data science, and business teams to define data requirements

Monitor and troubleshoot data pipeline health and performance

Develop Python or Scala code for complex transformations and data processing

Support Power BI and analytics teams with data modeling and performance optimization

Document data lineage, transformations, and technical architecture

Requirements


3+ years of professional data engineering or ETL/ELT development experience

Expert-level SQL skills with proven optimization experience

Proficiency in Python, Scala, or similar data processing languages

Hands-on experience with cloud data platforms (Azure Synapse, Snowflake, Databricks, or equivalent)

Understanding of healthcare data standards (HL7, FHIR, claims data structures)

Strong grasp of data modeling, normalization, and schema design

Experience with data versioning, CI/CD pipelines, and data quality frameworks


Preferred Qualifications


Experience with Microsoft Fabric or Azure Data Factory

Knowledge of HIPAA compliance and healthcare data security

Background in healthcare, RCM, or claims processing

Experience with dbt (data build tool) or equivalent transformation frameworks

Exposure to dimensional modeling and data warehousing best practices


What Success Looks Like


In 90 days: Deploy first cloud pipeline to production; complete HIPAA training; establish data quality baseline metrics

In 6 months: Reduce data pipeline latency by 30%; expand healthcare data models to include new sources; build reusable transformation components

Ongoing: Maintain 99.5%+ pipeline uptime; mentor junior engineers; drive architectural improvements for scale and performance

Apply