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Remote Data Processing Jobs in Ohio (NOW HIRING)

Greenfield Talent

Data Engineer (Remote)

Cleveland, OH · Remote

$111K - $133K/yr

We're looking for a Data Engineer to join our Data & Analytics team and take ownership of the data ... Document systems, processes, and decisions to build long‑term institutional knowledge What You ...

GRVTY

Software Engineer, Senior

Dayton, OH · On-site +1

$119K - $157K/yr

Background in signal processing, image processing, or remote sensing data workflows. * Experience with simulation, modeling, or mission analysis software in a defense or intelligence context.

GRVTY

Software Engineer, Senior

Dayton, OH · On-site +1

$119K - $157K/yr

Background in signal processing, image processing, or remote sensing data workflows. * Experience with simulation, modeling, or mission analysis software in a defense or intelligence context.

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Remote Data Processing information

How can I make 2000 a week working from home?

Remote data processing jobs can offer high earning potential, especially for experienced professionals who handle large datasets, use specialized tools, and meet project deadlines. To earn $2000 weekly, you may need to work multiple projects, develop strong skills in data analysis and processing, and possibly obtain relevant certifications. Consistent high-quality work and efficient time management are essential for reaching this income level remotely.

Are there real remote data entry jobs?

Yes, remote data entry jobs are available and involve inputting information into digital systems from home or other remote locations. These roles typically require basic computer skills, attention to detail, and sometimes familiarity with data management tools like spreadsheets or databases.

How to make $1000 a week remotely?

Remote data processing jobs can pay $1000 or more per week depending on experience, workload, and project complexity. To achieve this, professionals often work multiple projects, develop specialized skills in data analysis or automation, and utilize platforms that connect freelancers with clients. Consistent high-quality work and efficient time management are essential for reaching this income level.

What is the difference between Remote Data Processing vs Remote Data Analysis?

AspectRemote Data ProcessingRemote Data Analysis
Primary RoleHandling data input, cleaning, and preparationInterpreting data to generate insights and reports
Skills & CertificationsData management, SQL, basic scriptingStatistical analysis, data visualization, tools like Excel, R, Python
Work EnvironmentData warehouses, cloud platforms, databasesAnalysis tools, dashboards, reporting software
Industry UsageData management teams, IT departmentsBusiness intelligence, marketing, finance

Remote Data Processing focuses on preparing and managing raw data, while Remote Data Analysis involves interpreting that data to inform decisions. Both roles often require similar technical skills but differ in their core responsibilities and end goals.

What are some common challenges faced by professionals in remote data processing roles, and how can they be overcome?

Remote data processing professionals often encounter challenges such as ensuring data accuracy, managing large datasets, and maintaining clear communication with distributed teams. To overcome these, it's important to establish strong data validation protocols, use reliable tools for data management, and schedule regular virtual meetings to stay aligned with team objectives. Additionally, setting clear expectations and using collaborative platforms can help mitigate misunderstandings and improve workflow efficiency.

What jobs pay 4000 a week without a degree?

Remote data processing roles can pay around $4,000 per week for experienced professionals, especially those with strong skills in data analysis, programming, or automation. These jobs often require proficiency in tools like Python, SQL, or cloud platforms and may involve freelance or contract work with flexible schedules. High earnings typically depend on expertise, project complexity, and workload volume.

What is remote data processing?

Remote data processing refers to the collection, analysis, and management of data from a location outside of a traditional office setting, often using cloud-based tools and remote access technologies. Professionals in this role handle data entry, validation, organization, and sometimes basic analytics, ensuring data integrity and accessibility for organizations. This job typically requires strong computer skills, attention to detail, and the ability to work independently while maintaining data security and privacy protocols.

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

To thrive as a Remote Data Processing specialist, you need strong analytical skills, attention to detail, and proficiency in data entry and management, often supported by a relevant degree or experience in data-related roles. Familiarity with databases, spreadsheet software like Microsoft Excel or Google Sheets, and sometimes data processing tools such as SQL or Python is typically required. Excellent time management, self-motivation, and clear communication are essential soft skills for remote collaboration and meeting deadlines. These abilities ensure data accuracy, efficient processing, and effective teamwork in a remote work environment.
What are the most commonly searched types of Data Processing jobs in Ohio? The most popular types of Data Processing jobs in Ohio are:
What are popular job titles related to Remote Data Processing jobs in Ohio? For Remote Data Processing jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Remote Data Processing jobs in Ohio look for? The top searched job categories for Remote Data Processing jobs in Ohio are:
Remote Data Processing jobs near you
Infographic showing various Remote Data Processing job openings in Ohio as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution.

Data Engineer (Remote)

Greenfield Talent

Cleveland, OH • Remote

$111K - $133K/yr

Full-time

Re-posted 6 days ago

Job description

We’re looking for a Data Engineer to join our Data & Analytics team and take ownership of the data infrastructure that powers internal analytics, reporting, and operational insights. This is a hands‑on role where you’ll manage and evolve our ELT pipelines, Snowflake environment, and Python‑based integrations while partnering closely with analysts and systems administrators who rely on high‑quality, reliable data.

What You’ll Do

  • Own the day‑to‑day operation, maintenance, and enhancement of ELT pipelines and the Snowflake data warehouse

  • Troubleshoot and resolve pipeline failures, data quality issues, and performance bottlenecks

  • Design, build, and document new data models and transformations as analytical needs evolve

  • Ensure data reliability, consistency, and availability for downstream consumers

  • Support and extend API integration workflows built with Boomi and Python

  • Maintain and contribute to custom Python applications used across the team

  • Collaborate with internal stakeholders to scope and deliver new data integration projects

  • Participate in evaluating modern data tooling as we consider improvements to our architecture

  • Document systems, processes, and decisions to build long‑term institutional knowledge

What You Bring

  • Bachelor’s degree in Computer Science, Information Systems, Statistics, or a related field (preferred)

  • 3–5 years of hands‑on experience in a data engineering role

  • Strong SQL skills and a solid understanding of data modeling for analytics

  • Practical experience with Snowflake or a similar cloud data warehouse

  • Familiarity with ELT/ETL concepts and tools (WhereScape RED, Matillion, Airbyte, dbt, etc.)

  • Working knowledge of Python for data processing and scripting

  • Experience with REST APIs and integrating external data sources

  • Comfort digging into unfamiliar systems to diagnose root‑cause issues

  • Experience using GitHub for version control

Nice to Have

  • Exposure to enterprise integration platforms (Boomi or similar iPaaS tools)

  • Experience with Oracle EBS or Salesforce

  • Familiarity with data pipeline orchestration concepts

  • Experience partnering closely with BI or analytics teams