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Remote Data Jobs in Springfield, MA (NOW HIRING)

EnthuZiastic

Growth Hacker - Remote

Springfield, MA · Remote

... a remote position. User Acquisition: * Develop and execute strategies to acquire new users ... Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and ...

Quest Global

Aftermarket Field Rep- Remote

Windsor, CT · Remote

$29 - $31/hr

Review data discrepancies and gaps across multiple systems. Escalate to appropriate channels. What You Will Bring: Supply ChainManagement aspects: * History of customer facing interaction

EnthuZiastic

Growth Hacker - Remote

Hartford, CT · Remote

... a remote position. User Acquisition: * Develop and execute strategies to acquire new users ... Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and ...

Quest Global

Aftermarket Field Rep- Remote

Windsor, CT · On-site +1

$29 - $31/hr

Review data discrepancies and gaps across multiple systems. Escalate to appropriate channels. What You Will Bring: Supply Chain Management aspects: * History of customer facing interaction

Quest Global

Aftermarket Field Rep- Remote

Windsor, CT · Remote

$29 - $31/hr

Review data discrepancies and gaps across multiple systems. Escalate to appropriate channels. What You Will Bring: Supply Chain Management aspects: * History of customer facing interaction

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Showing results 1-20

All JobsRemote Data JobsRemote Data Jobs in Springfield, MA

Remote Data information

See Springfield, MA salary details

$45.8K

$164.4K

$242.6K

How much do remote data jobs pay per year?

As of Jun 19, 2026, the average yearly pay for remote data in Springfield, MA is $164,441.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,000.00 and $169,400.00 per year, depending on experience, location, and employer.

What are some common challenges faced when working as a Remote Data Analyst, and how can they be addressed?

Remote Data Analysts often face challenges such as maintaining effective communication with team members, managing access to secure data, and staying aligned with project goals across different time zones. These can be addressed by leveraging collaboration tools like Slack or Microsoft Teams, following strict data security protocols, and participating in regular virtual meetings to ensure everyone is on the same page. Proactive communication and strong organizational skills are key to thriving in a remote data role.

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

AspectRemote DataRemote Data Analyst
Required CredentialsBachelor's in Data Science, Computer Science, or related field; knowledge of databases and data toolsBachelor's in Data Science, Statistics, or related; proficiency in data analysis tools like Excel, SQL, and visualization software
Work EnvironmentRemote, often independent, with collaboration via online platformsRemote, involves analyzing data sets, creating reports, and communicating findings
Employer & Industry UsageTech companies, finance, healthcare, and e-commerceBusiness, marketing, finance, and tech sectors

Remote Data generally refers to roles focused on managing and processing data, while Remote Data Analyst emphasizes analyzing data to generate insights. Both roles often require similar educational backgrounds and work remotely, but Data Analysts typically focus more on interpreting data and creating reports for decision-making.

How can I make 2000 a week working from home?

Remote data roles such as data analyst or data scientist can offer high earning potential, especially with specialized skills in programming, statistics, and tools like SQL or Python. To reach $2000 weekly, professionals often need extensive experience, a strong portfolio, and may work as freelancers or in consulting, often requiring a full-time schedule or multiple projects simultaneously.

What job makes $10,000 a month without a degree?

Remote data-related roles such as data analyst, data engineer, or freelance data consultant can potentially earn $10,000 or more per month without a formal degree, especially with strong skills in SQL, Python, or data visualization tools. Success in these roles often depends on experience, portfolio, and the ability to secure high-paying clients or positions, rather than formal education alone.

How to make $1000 a week remotely?

Remote data-related jobs such as data analysis, data entry, or data management can offer opportunities to earn $1000 weekly, especially with high-demand skills like SQL, Excel, or Python. Achieving this income typically requires consistent work, specialized skills, and possibly freelance or contract work arrangements that pay per project or hourly rates of $25-$50 or more.

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 background in data science or a related field. Familiarity with data analysis tools such as Python, R, SQL, and platforms like Tableau or Power BI, along with relevant certifications, is typically required. Excellent self-motivation, time management, and communication skills help you stand out in a remote environment. These capabilities are crucial for delivering accurate insights, collaborating effectively from a distance, and meeting business objectives efficiently.

Is 40 too late for data science?

Age is not a barrier to entering data science, and many professionals successfully transition into the field at age 40 or later. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, and building a strong portfolio. Employers value experience and problem-solving ability, making it possible to start a data science career at any age with dedication.

What are remote data jobs?

Remote data jobs are positions that involve collecting, analyzing, managing, or interpreting data while working from a location outside the traditional office environment. These roles can include data analysts, data scientists, data entry specialists, and database administrators, among others. Remote data professionals use online tools and platforms to access and process data, collaborate with teams, and deliver insights or reports. This flexible work arrangement allows individuals to contribute to data-driven projects from anywhere with an internet connection.
What are the most commonly searched types of Data jobs in Springfield, MA? The most popular types of Data jobs in Springfield, MA are:
What are popular job titles related to Remote Data jobs in Springfield, MA? For Remote Data jobs in Springfield, MA, the most frequently searched job titles are:
What job categories do people searching Remote Data jobs in Springfield, MA look for? The top searched job categories for Remote Data jobs in Springfield, MA are:
What cities near Springfield, MA are hiring for Remote Data jobs? Cities near Springfield, MA with the most Remote Data job openings:
Remote Data jobs near you
Infographic showing various Remote Data job openings in Springfield, MA as of June 2026, with employment types broken down into 90% Full Time, 9% Part Time, and 1% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $164,441 per year, or $79.1 per hour.

Senior Python Data Engineer

Accord Technologies Inc.

Hartford, CT • Remote

$117K - $140K/yr

Contractor

Posted 15 days ago

Job description

Job Title: Sr. Python Data Engineer (Python, MongoDB, PowerBI and Data Extraction, ability to write code)
Location: Hartford, CT
Position type: W2 contract 
Duration: 12+ months extendable.
Mandatory skills:
Strong Python candidate having exp in Mondo DB, PowerBI and Data ExtractionOverview

We are seeking a motivated and skilled Data Engineer to join our team. The ideal candidate will have strong proficiency in Python, knowledge of MongoDB, and experience with Power BI. This role will primarily focus on building data extracts and data feeds for downstream systems, including Ledger, Reporting, and Boudreaux. You will be responsible for writing the code necessary to deliver the required data based on predefined definitions

Responsibilities:

  •  Data Extraction and Transformation: Write efficient and scalable Python code to extract and transform data from various sources, ensuring it meets the requirements for downstream systems.
  • MongoDB Management: Utilize MongoDB for storing and managing data. Design and optimize data models and queries to ensure high performance and reliability.
  • Power BI Integration: Collaborate with stakeholders to deliver data in a format suitable for reporting and visualization in Power BI. Ensure that the data aligns with business needs and reporting requirements.
  • Data Feed Development: Develop and maintain data feeds for downstream systems, including Ledger and Boudreaux, ensuring timely and accurate data delivery.
  • Collaboration with Stakeholders: Work closely with business analysts and other stakeholders to understand data definitions and requirements, translating them into technical specifications.
  • Documentation: Maintain comprehensive documentation of data pipelines, data models, and technical specifications to support knowledge sharing and compliance.
  • Quality Assurance: Implement data validation and quality checks to ensure the accuracy and integrity of the data being delivered.

Requirements:

  • Bachelor’s degree in Computer Science, Data Engineering, Information Technology, or a related field.
  • Minimum of 9 years of experience in data engineering or a related field.
  • Strong experience in Python programming, particularly in data manipulation and ETL processes.
  • Solid knowledge of MongoDB and experience in database design and management.
  • Familiarity with Power BI for creating reports and dashboards.
  • Experience in building data extracts and feeds for business applications.
  • Analytical Skills: Strong analytical and problem-solving skills with a focus on delivering high-quality data solutions.
  • Communication: Excellent verbal and written communication skills, with the ability to clearly convey technical concepts to both technical and non-technical stakeholders.
  • Team Player: Ability to work collaboratively in a fast-paced, team-oriented environment.