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Remote Databricks Data Engineer Jobs in Atlanta, GA

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 ... AWS, Azure, Databricks, and Snowflake; RDBMS: Teradata, Oracle, DB2, SQL Server; Scripting ...

Kemper

Data Quality Engineer

Alpharetta, GA · Remote

$111K - $134K/yr

... Remote-OH, Remote-PA, Remote-RI, Remote-VA Details Kemper is one of the nation's leading ... Kemper is seeking a Data Quality Engineer specializing in Data Testing and Quality Engineering to ...

Siemens Healthineers

AI LLM Engineer

Atlanta, GA · On-site +1

You will partner with business stakeholders, data engineers, and platform teams to build production ... This role is designed to be onsite in Atlanta, Georgia with some remote/hybrid flexibility* What ...

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All JobsDatabricks Data Engineer JobsRemote Databricks Data Engineer JobsRemote Databricks Data Engineer Jobs in Atlanta, GA

Remote Databricks Data Engineer information

See Atlanta, GA salary details

$42.8K

$124.7K

$170.7K

How much do remote databricks data engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for remote databricks data engineer in Atlanta, GA is $124,743.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,100.00 and $132,200.00 per year, depending on experience, location, and employer.

What is a remote Databricks data engineer?

A Remote Databricks Data Engineer is a professional who designs, develops, and manages large-scale data processing systems using the Databricks platform, often working from a remote location. They focus on building data pipelines, integrating data sources, and optimizing workflows for analytics and machine learning, leveraging tools like Apache Spark within Databricks. These engineers collaborate with data scientists, analysts, and other stakeholders to ensure data is accessible, reliable, and scalable for business needs. Remote roles offer flexibility in work location while still requiring strong communication and technical skills.

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

To thrive as a Remote Databricks Data Engineer, you need a solid background in data engineering, strong programming skills in Python or Scala, and experience with big data frameworks, often supported by a degree in computer science or a related field. Proficiency with Databricks, Apache Spark, cloud platforms (such as AWS or Azure), and relevant certifications like Databricks Certified Data Engineer are highly valuable. Strong problem-solving abilities, effective remote communication, and collaboration skills set top performers apart in distributed teams. These skills and qualities ensure efficient data pipeline development, seamless integration, and successful project delivery in remote environments.

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

Remote Databricks Data Engineers often encounter challenges such as coordinating efficiently with distributed teams, managing access to secure data environments, and ensuring smooth pipeline deployments across different cloud platforms. To overcome these, it's important to leverage communication tools for regular check-ins, follow strict data governance protocols, and utilize collaborative features in Databricks such as shared notebooks and version control. Proactively documenting your work and staying updated with platform updates can also help streamline remote collaboration and problem-solving.

What are the most commonly searched types of Databricks Data Engineer jobs in Atlanta, GA?

The most popular types of Databricks Data Engineer jobs in Atlanta, GA are:

What are popular job titles related to Remote Databricks Data Engineer jobs in Atlanta, GA?

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

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

The top searched job categories for Remote Databricks Data Engineer jobs in Atlanta, GA are:

What cities near Atlanta, GA are hiring for Remote Databricks Data Engineer jobs?

Cities near Atlanta, GA with the most Remote Databricks Data Engineer job openings:

Remote Databricks Data Engineer jobs near you
Infographic showing various Remote Databricks Data Engineer job openings in Atlanta, GA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 8% Hybrid, and 92% Remote job distribution, with an average salary of $124,743 per year, or $60 per hour.

Junior Data Engineer

Atlanta, GA • On-site, Remote

Sequoia Connect
See more jobs at Sequoia Connectexternal

Full-time

Re-posted 15 hours ago

Job description

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/
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.

Apply