Entry Level Junior Data Engineer information
See salary details
$33.5K - $40.4K
3% of jobs
$40.4K - $47.3K
20% of jobs
$48.8K is the 25th percentile. Wages below this are outliers.
$47.3K - $54.2K
7% of jobs
$54.2K - $61.1K
6% of jobs
The median wage is $68.5K / yr.
$68K - $75K
17% of jobs
$78.6K is the 75th percentile. Wages above this are outliers.
$75K - $81.9K
17% of jobs
$81.9K - $88.8K
7% of jobs
$88.8K - $95.7K
4% of jobs
$95.7K - $102.6K
3% of jobs
$102.6K - $109.5K
2% of jobs
How much do entry level junior data engineer jobs pay per year?
As of Sep 12, 2026, the average yearly pay for entry level junior data engineer in the United States is $71,799.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,500.00 and $80,000.00 per year, depending on experience, location, and employer.
An Entry Level Junior Data Engineer helps build and maintain the systems that collect, store, and process large amounts of data for a company. They typically assist in setting up data pipelines, cleaning and organizing raw data, and supporting more senior data engineers in managing databases and cloud storage solutions. Their work ensures that data is accessible, reliable, and ready for analysis by data scientists and analysts. Junior data engineers often use programming languages like Python or SQL and may work with big data tools such as Hadoop or Spark.
To thrive as an Entry Level Junior Data Engineer, you need a solid understanding of programming languages (such as Python or SQL), data modeling, and database systems, usually backed by a relevant degree or coursework. Familiarity with data warehousing tools, ETL pipelines, and platforms like AWS or Azure is commonly expected, along with experience using version control systems like Git. Attention to detail, problem-solving abilities, and effective communication are vital soft skills for collaborating with teams and handling data issues. These skills and qualities ensure data integrity, efficient workflow, and successful support of business intelligence initiatives.
One common challenge for Entry Level Junior Data Engineers is adapting to the complexity and scale of real-world data systems, which often involve messy, incomplete, or inconsistent data from multiple sources. Unlike academic projects, production environments require strict attention to data quality, security, and efficient processing. Junior engineers may also need to learn how to work within established team workflows, use version control, and collaborate closely with data scientists, analysts, and senior engineers to support business objectives. Building strong communication skills and proactively asking for feedback can help overcome these initial hurdles and accelerate professional growth.
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