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Remote Data Engineer Jobs in Powder Springs, GA (NOW HIRING)

Sequoia Connect

Junior Data Engineer

Atlanta, GA · Remote

We are currently searching for a Junior Data Engineer: The Challenge (Responsibilities) * Assist in ... Remote If you meet these qualifications and are pursuing new challenges, start your application on ...

Sequoia Connect

Junior Data Engineer

Atlanta, GA · On-site +1

We are currently searching for a Junior Data Engineer: The Challenge (Responsibilities) * Assist in ... Remote If you meet these qualifications and are pursuing new challenges, start your application on ...

PadSplit

Data Engineer (Fully Remote)

Atlanta, GA · On-site +1

$150K - $165K/yr

The Role We Need PadSplit is growing its analytics platform and needs a hands-on Data Engineer to ... Fully remote position - we swear! * Competitive compensation package including an equity incentive ...

FAVARH

Senior Data Engineer

Atlanta, GA · On-site +1

$101K - $138K/yr

Implement enterprise solutions, in a cloud environment, using a vast range of data engineering and cloud technologies. Work on tasks independently and seek guidance from leaders as needed. Help ...

KPI Solutions

Supply Chain Data Analyst

Atlanta, GA · On-site +1

Advanced Solution Development Data Scientist/Senior Data Engineer (Data+AI / Databricks / SQL) - Closed-Loop Design & Pre-Sales Automation KPI Solutions is a leading supply chain and warehouse ...

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All JobsData Engineer JobsRemote Data Engineer JobsRemote Data Engineer Jobs in Powder Springs, GA

Remote Data Engineer information

See Powder Springs, GA salary details

$42.1K

$122.8K

$168.1K

How much do remote data engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for remote data engineer in Powder Springs, GA is $122,832.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,400.00 and $130,200.00 per year, depending on experience, location, and employer.

What is a remote data engineer?

A Remote Data Engineer is a professional who designs, builds, and maintains data pipelines, databases, and data processing systems while working from a location outside of a traditional office. They collaborate with data scientists, analysts, and other stakeholders to ensure data is collected, stored, and made accessible efficiently and securely. Remote Data Engineers use programming languages like Python or Scala, work with technologies such as SQL, Hadoop, or cloud platforms, and address challenges related to data quality and scalability. Their remote role allows them to work for companies regardless of geographic location, often relying on virtual collaboration tools to stay connected with their teams.

What does a remote data engineer do?

As a remote data engineer, you focus on collecting, storing, and organizing large amounts of information. You work from home to design, develop, and maintain systems for the mining, warehousing, and processing of data. A data engineer communicates with employers, clients, or other data professionals to assess the needs of the project and develop and implement solutions to meet those needs. Data engineers also take steps to manage current database architecture and make updates when needed. Remote engineers typically handle their responsibilities in a cloud-based environment using “big data” tools, such as Amazon Web Services (AWS) and SQL.

What are the key skills and qualifications needed to thrive as a remote data engineer, and why are they important?

To thrive as a Remote Data Engineer, you need strong programming skills in languages like Python or Scala, expertise in SQL, data modeling, and a background in computer science or a related field. Familiarity with cloud platforms (such as AWS, Azure, or GCP), big data tools (like Hadoop and Spark), and certifications in cloud or data engineering are highly valued. Excellent problem-solving, communication, and self-management skills help remote data engineers collaborate effectively and stay productive in a distributed environment. These competencies ensure reliable data pipelines, scalable solutions, and seamless teamwork, which are critical for organizational success in data-driven projects.

How do remote data engineers typically collaborate with other team members across different time zones?

Remote Data Engineers often work with cross-functional teams, including data scientists, analysts, and software engineers, many of whom may be located in different parts of the world. Collaboration is usually facilitated through project management tools, version control platforms, and regular virtual meetings. It’s common to have a mix of synchronous check-ins and asynchronous communication, allowing for flexible scheduling and efficient handoffs. Strong written communication skills and proactive status updates are essential for staying aligned with team objectives and project deadlines.

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

AspectRemote Data EngineerRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related; SQL, Python, cloud certificationsBachelor's in Statistics, Data Science, or related; SQL, Excel, visualization tools
Work EnvironmentCollaborates with data engineering teams, cloud platforms, big data toolsWorks with business teams, dashboards, reporting tools
Industry UsageTech, finance, healthcare, e-commerceMarketing, finance, retail, healthcare
Common Search IntentBuilding data pipelines, data infrastructureData reporting, insights, visualization

Remote Data Engineers focus on designing and maintaining data pipelines and infrastructure, often requiring programming and cloud skills. Remote Data Analysts interpret data, create reports, and provide insights using visualization tools. While both roles work with data, their responsibilities and skill sets differ, making each suited for different career paths within data teams.

Are remote data engineers still in demand?

Remote data engineers are currently in high demand due to the increasing reliance on data-driven decision making and cloud-based data platforms. Skills in SQL, Python, cloud services, and data pipeline tools are highly sought after, and many organizations continue to hire for remote roles to access a broader talent pool.

Can a remote data engineer work remotely?

Yes, remote data engineers can work remotely, as the role primarily involves managing data pipelines, databases, and cloud-based tools that can be accessed from anywhere with an internet connection. Many companies offer remote positions for data engineers, often requiring skills in SQL, Python, cloud platforms, and data architecture. However, some roles may require occasional on-site presence or specific certifications depending on the employer's policies.
More about Remote Data Engineer jobs

What are the most commonly searched types of Data Engineer jobs in Powder Springs, GA?

The most popular types of Data Engineer jobs in Powder Springs, GA are:

What are popular job titles related to Remote Data Engineer jobs in Powder Springs, GA?

For Remote Data Engineer jobs in Powder Springs, GA, the most frequently searched job titles are:

What job categories do people searching Remote Data Engineer jobs in Powder Springs, GA look for?

The top searched job categories for Remote Data Engineer jobs in Powder Springs, GA are:

What cities near Powder Springs, GA are hiring for Remote Data Engineer jobs?

Cities near Powder Springs, GA with the most Remote Data Engineer job openings:

Remote Data Engineer jobs near you
Infographic showing various Remote Data Engineer job openings in Powder Springs, GA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 11% Part Time, and 5% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $122,832 per year, or $59.1 per hour.

Junior Data Engineer

Sequoia Connect

Atlanta, GA • Remote

Full-time

Posted 27 days ago

Job description

At Sequoia Connect, we are a Talent-First Technology Ecosystem that redefines how elite professionals interact with the global digital landscape. We move beyond traditional models to act as a catalyst for the top 1% of global talent, connecting human potential with complex industrial execution. By joining our inner circle, you are not simply taking a position; you are aligning with a strategic partner dedicated to updating your "Human OS" and accelerating your growth through world-class, high-impact projects.

We are currently partnering with a rapidly growing, automation-led powerhouse that serves 31 Fortune 500 companies across the financial, healthcare, and manufacturing sectors. With a global workforce of over 32,000 employees and a presence in 28 countries, our client is a titan of digital transformation. Their "Automate Everything, Cloudify Everything" strategy ensures you will be working at the absolute forefront of AI-driven automation and cloud solutions.

This is your chance to thrive in a "Customer Success, First and Always" environment that prizes continuous learning and radical ownership. You will collaborate within an international network of expertise across 39 delivery centers worldwide, gaining exposure to complex engineering challenges that redefine industrial standards. If you are a driven professional looking for a dynamic, forward-thinking workplace where your growth is the priority, this is where you belong.

We are currently searching for a Junior Data Engineer:

The Challenge (Responsibilities)

  • Assist in building and maintaining ETL pipelines using Python and PySpark.
  • Support the development of workflows utilizing AWS Glue, Lambda, and Step Functions.
  • Work extensively with cloud data storage platforms, including S3, Redshift, RDS, and Oracle.
  • Write complex SQL queries for data extraction, transformation, validation, and reporting.
  • Help implement basic monitoring, logging, and error handling for data pipelines.
  • Support the ingestion and processing of data from APIs and JSON payloads.
  • Collaborate with software engineers, data analysts, and business stakeholders to understand requirements.
  • Contribute to code management, technical documentation, and deployment support activities.

Your Profile (Requirements)

  • Degree holders for the visa application process.
  • 0 to 4 years of software development or data engineering experience across relevant cloud platforms.
  • Good knowledge of Python and SQL.
  • Solid understanding of AWS services, specifically S3, SNS/SQS, EMR, Glue, Lambda, Redshift, and Step Functions.
  • Strong grasp of ETL concepts and data processing fundamentals.
  • Familiarity with GitLab, Terraform, and the Software Development Life Cycle (SDLC) from development to production.
  • Familiarity with PySpark, AWS managed services, data engineering best practices, and code optimization.
  • High-Performance Mindset: Resilience, emotional intelligence, and a focus on agile delivery.
  • Technologist DNA: A deep understanding of the difference between "coding" and "engineering."

Desired

  • Exposure to PySpark, Athena, CloudWatch, SNS, and SQS.
  • Internship, project, or academic experience specifically in cloud computing, analytics, or data engineering.
  • Familiarity with cloud-native foundations or AI coding assistants (e.g., GitHub Copilot).

Languages

  • Advanced Oral English: For seamless collaboration with global teams.
  • Advanced Spanish.

Special Notes

  • Our Client is seeking candidates focused on foundational skill-building in a dynamic cloud environment.

Work Arrangement

We value flexibility to support your lifestyle. This position is available as:

  • Remote


If you meet these qualifications and are pursuing new challenges, start your application on our website to join an award-winning employer. Explore all our job openings | Sequoia Career’s Page: https://www.sequoia-connect.com/careers/


Keywords:
Phyton, SQL, PySpark, AWS Glue, ETL
Requirements:
  • 0-4 years of software development experience across the appropriate platform.
  • Good knowledge on Python and SQL.
  • Good understanding to AWS services such as S3, SNS/SQS, EMR, Glue, Lambda, Redshift, and Step Functions.
  • Good understanding of ETL concepts and data processing fundamentals.
  • Familiarity with GitLab/Terraform and SDLC from development to production.
  • Familiarity to PySpark, AWS managed services, data engineering best practices, and code optimization.
  • Good analytical, problem-solving, and communication skills.