Entry Level Data Engineer Remote information
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$44.5K - $56.6K
0% of jobs
$56.6K - $68.7K
1% of jobs
$68.7K - $80.8K
3% of jobs
$80.8K - $92.9K
4% of jobs
$115.5K is the 25th percentile. Wages below this are outliers.
$105K - $117K
11% of jobs
$117K - $129.1K
12% of jobs
The median wage is $132.4K / yr.
$129.1K - $141.2K
45% of jobs
$141.2K - $153.3K
8% of jobs
$153.3K - $165.4K
5% of jobs
$165.4K - $177.5K
3% of jobs
How much do entry level data engineer remote jobs pay per year?
As of Aug 21, 2026, the average yearly pay for entry level data engineer remote in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.
An Entry Level Data Engineer (Remote) is a professional who helps build and maintain systems for collecting, storing, and analyzing large sets of data, all while working from a location outside of a traditional office. They typically assist with tasks like setting up data pipelines, cleaning raw data, and supporting data infrastructure. These roles often require basic programming skills in languages such as Python or SQL, familiarity with cloud platforms, and a foundational understanding of databases. Working remotely, they collaborate with teams using digital communication tools to ensure data is accessible and reliable for analysis.
To thrive as an Entry Level Data Engineer (Remote), you need a solid understanding of data structures, SQL, and programming languages like Python or Java, often supported by a relevant degree in computer science or a related field. Familiarity with cloud platforms (e.g., AWS, Azure), ETL tools, and version control systems like Git is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with distributed teams. These skills ensure you can efficiently manage data pipelines, maintain data quality, and contribute effectively in a remote work environment.
Entry-level data engineers working remotely often face challenges such as limited access to immediate mentorship, difficulties in understanding existing data infrastructure, and coordinating effectively with cross-functional teams. Overcoming these challenges involves proactive communication—regularly checking in with team members and asking for clarification when needed. Utilizing collaborative tools, documenting your work thoroughly, and participating in virtual knowledge-sharing sessions can help you stay connected and continue learning in a remote setting.
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