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Remote Entry Level Data Engineering Jobs in Jefferson, GA

Remote micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their ... clinical data sources. * Provide expert insights on structure-activity and structure-property ...

... engineering teams through advanced 3D modeling and coordination. This role involves creating and ... This position is eligible to be fully remote or for work out of our Lexington, KY HQ or our ...

... data governance policies and meet ADA Title II compliance requirements. Local candidates strongly preferred but 100% remote is acceptable. The consultant will be responsible for additional Power BI ...

Remote Entry Level Data Engineering information

See Jefferson, GA salary details

$41.1K

$120K

$164.1K

How much do remote entry level data engineering jobs pay per year?

As of Aug 18, 2026, the average yearly pay for remote entry level data engineering in Jefferson, GA is $119,951.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,900.00 and $127,100.00 per year, depending on experience, location, and employer.

What is a remote entry level data engineer?

A remote entry level data engineer is a professional who works from a location outside of a traditional office setting to help design, build, and maintain the data infrastructure and pipelines needed for organizations to collect and analyze data. These roles are suitable for individuals new to the field, often requiring foundational knowledge in programming, databases, and data processing tools. Entry level data engineers typically work under the guidance of more experienced team members and focus on tasks such as data cleaning, basic ETL (extract, transform, load) processes, and supporting data integration projects. Working remotely allows for flexibility and collaboration using digital communication tools.

What are the key skills and qualifications needed to thrive as a remote entry level data engineer?

To thrive as a Remote Entry Level Data Engineer, you need a foundational understanding of databases, data modeling, and programming languages such as Python or SQL, often supported by a relevant degree or coursework. Familiarity with cloud platforms (like AWS or Azure), ETL tools, and version control systems (such as Git) is typically required. Strong problem-solving skills, attention to detail, and effective virtual communication are essential soft skills for remote collaboration and troubleshooting. These skills ensure efficient data pipeline development, data integrity, and productive teamwork in distributed engineering environments.

What are some common challenges faced by remote entry level data engineers, and how can they be addressed?

Remote entry level data engineers often face challenges such as limited hands-on mentorship, understanding complex data pipelines, and collaborating across different time zones. To overcome these, it's helpful to proactively communicate with your team, seek feedback regularly, and make use of virtual collaboration tools. Participating in team meetings, asking questions, and accessing available documentation will help you build confidence and stay aligned with project goals.

What is the difference between Remote Entry Level Data Engineering vs Remote Junior Data Analyst?

AspectRemote Entry Level Data EngineeringRemote Junior Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; basic SQL and programming skillsBachelor's in related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, cloud platforms, data pipelinesReporting, data interpretation, dashboards
Industry UsageTech, finance, healthcare, e-commerceMarketing, retail, finance, healthcare

Remote Entry Level Data Engineering focuses on building data pipelines and managing data infrastructure, requiring technical skills like SQL and programming. Remote Junior Data Analysts interpret data, create reports, and support decision-making. While both roles involve working with data remotely, data engineers handle data infrastructure, whereas data analysts focus on analyzing and visualizing data to provide insights.

Can I work remotely as a remote entry level data engineer?

Yes, many entry-level data engineering roles are available as remote positions, especially with the rise of cloud-based tools like AWS, Azure, and GCP. These jobs typically require knowledge of SQL, Python, and data pipeline tools, and often offer flexible schedules for remote work.

What job categories do people searching Remote Entry Level Data Engineering jobs in Jefferson, GA look for?

The top searched job categories for Remote Entry Level Data Engineering jobs in Jefferson, GA are:

What cities near Jefferson, GA are hiring for Remote Entry Level Data Engineering jobs?

Cities near Jefferson, GA with the most Remote Entry Level Data Engineering job openings:

Infographic showing various Remote Entry Level Data Engineering job openings in Jefferson, GA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $119,951 per year, or $57.7 per hour.

Digital Chemistry Specialist - Remote

micro1 AI

Athens, GA • Remote

$90 - $120/hr

Part-time

Posted 21 days ago


Job description

Role Title: Bioinformatics Scientist


Role Type: Contractor


Location: Remote


micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze complex datasets related to medicinal chemistry using advanced bioinformatics methodologies.
  2. Provide detailed scientific input and content to support the development and training of AI models.
  3. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis.
  4. Evaluate and synthesize findings from biological, chemical, and clinical data sources.
  5. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry.
  6. Assess AI-generated outputs for scientific accuracy, relevance, and reliability.
  7. Deliver comprehensive written feedback and actionable recommendations for model improvement.


Preferred Qualifications

  1. Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline.
  2. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles.
  3. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.
  4. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME).
  5. Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts.
  6. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science.
  7. Experience collaborating in multidisciplinary or remote project environments is advantageous.