ZipRecruiter

Log In

1

Data Analyst Jobs in Barre, VT (NOW HIRING)

Trioptus

DataOps Engineer

Montpelier, VT · On-site

This role focuses on building and operationalizing modern data quality, governance, analytics, and performance monitoring capabilities within an enterprise data environment. The ideal candidate will ...

All JobsData Analyst JobsData Analyst Jobs in Barre, VT

Data Analyst information

See Barre, VT salary details

$33.4K

$81.1K

$133.5K

How much do data analyst jobs pay per year?

As of Sep 1, 2026, the average yearly pay for data analyst in Barre, VT is $81,140.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,400.00 and $95,200.00 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 Barre, VT?

The most popular types of Data Analyst jobs in Barre, VT are:

What cities near Barre, VT are hiring for Data Analyst jobs?

Cities near Barre, VT with the most Data Analyst job openings:

Data Analyst jobs near you
Infographic showing various Data Analyst job openings in Barre, VT as of August 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% In-person job distribution, with an average salary of $81,140 per year, or $39 per hour.

DataOps Engineer

Trioptus

Montpelier, VT • On-site

Contractor

Re-posted 2 days ago

Job description

Job Title: DataOps Engineer

Job Type: Contract

Duration: 12–15 months (with potential for extension)

Work Location: Remote (U.S.-based)

Work Hours: Standard business hours

Job Overview

We are seeking an experienced DataOps Engineer to support a large‑scale healthcare data modernization initiative. This role focuses on building and operationalizing modern data quality, governance, analytics, and performance monitoring capabilities within an enterprise data environment.

The ideal candidate will combine strong technical expertise with the ability to collaborate closely with internal teams through hands‑on delivery, documentation, and knowledge transfer. The engagement emphasizes long‑term sustainability, staff enablement, and repeatable best practices rather than one‑time development.

Key Responsibilities

DataOps & Data Quality

  • Develop and maintain data quality rules, validation frameworks, and monitoring processes
  • Implement statistical process control (SPC) and anomaly detection to ensure data reliability
  • Support incident logging, triage, root‑cause analysis, and continuous improvement efforts

Data Governance & Metadata

  • Define and maintain metadata standards, data glossary entries, and end‑to‑end data lineage
  • Establish governance procedures, SOPs, and disclosure/suppression rules
  • Translate downstream analytics and governance requirements into clear upstream data specifications

Analytics & Business Intelligence

  • Design and support governed semantic data models
  • Assist with the development and validation of standardized dashboards and reports
  • Ensure data accuracy, refresh reliability, and compliance with governance standards

Platforms & Tools

  • Work within platforms such as Azure DevOps, cloud‑based data lakes, and BI tools
  • Maintain operational dashboards, KPIs, and performance metrics
  • Support agile workflows, documentation repositories, and collaboration tools

Enablement & Collaboration

  • Partner with internal teams through hands‑on co‑development sessions
  • Create and maintain Wikis, runbooks, and playbooks for long‑term ownership
  • Deliver role‑based training and support organizational readiness initiatives

Required Qualifications

  • Proven experience as a DataOps Engineer, Data Engineer, Analytics Engineer, or similar role
  • Strong background in data quality engineering, governance, and analytics enablement
  • Experience with:
    • Azure DevOps or similar workflow tools
    • Business intelligence platforms (e.g., Power BI or equivalent)
    • Cloud data platforms (Azure, AWS, or similar)
  • Experience working in Agile or iterative delivery environments
  • Strong documentation, communication, and stakeholder collaboration skills
  • Ability to work independently in a remote environment

Preferred Qualifications

  • Certifications such as:
    • Azure Data Engineer
    • Power BI Data Analyst
    • Databricks Data Engineer
    • Data Governance or Data Management certifications
  • Experience in healthcare, public sector, or highly regulated data environments
  • Familiarity with change management and operational enablement practices
     

    #DataOps #DataEngineering #CloudData #AzureDevOps #PowerBI #DataGovernance #AnalyticsJobs