Data Infrastructure Engineer Salary in United States during 2024

Salary details

The average Data Infrastructure Engineer salary lies between USD 150,000 and USD 225,000 in the United States. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Nov. 17, 2024

Salary trend

Top 20 Job Tags for Data Infrastructure Engineer roles

The three most common job tag items assiciated with Data Infrastructure Engineer job listings are Engineering, Python and Pipelines. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

Engineering | 57 jobs Python | 56 jobs Pipelines | 45 jobs AWS | 43 jobs Spark | 41 jobs Security | 40 jobs Kubernetes | 38 jobs Kafka | 36 jobs Data pipelines | 35 jobs Architecture | 33 jobs Java | 33 jobs SQL | 30 jobs Terraform | 29 jobs Big Data | 26 jobs GCP | 26 jobs Azure | 26 jobs Docker | 25 jobs Computer Science | 25 jobs Machine Learning | 22 jobs DevOps | 22 jobs

Top 20 Job Perks/Benefits for Data Infrastructure Engineer roles

The three most common job benefits and perks assiciated with Data Infrastructure Engineer job listings are Career development, Health care and Equity / stock options. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 51 jobs Health care | 42 jobs Equity / stock options | 40 jobs Flex vacation | 26 jobs Startup environment | 26 jobs Flex hours | 24 jobs Competitive pay | 23 jobs Insurance | 22 jobs Parental leave | 21 jobs Team events | 20 jobs Salary bonus | 15 jobs Medical leave | 14 jobs Unlimited paid time off | 11 jobs Wellness | 9 jobs Relocation support | 9 jobs 401(k) matching | 6 jobs Gear | 6 jobs Home office stipend | 6 jobs Fertility benefits | 6 jobs Conferences | 3 jobs

Salary Composition for Data Infrastructure Engineers

In the United States, the salary composition for a Data Infrastructure Engineer typically includes a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Performance bonuses can vary significantly, often comprising 10% to 20% of the total salary, depending on the company's performance and individual contributions. Additional remuneration, such as stock options, is more common in larger tech companies and startups, where it can make up 5% to 15% of the total compensation. The exact composition can vary based on the region, with tech hubs like Silicon Valley offering higher equity components, and industry, with finance and healthcare sectors sometimes offering higher bonuses.

Steps to Increase Salary

To increase your salary further from the position of a Data Infrastructure Engineer, consider the following strategies:

• Specialize in High-Demand Skills: Focus on acquiring expertise in cutting-edge technologies such as cloud computing, big data analytics, or machine learning infrastructure.
• Pursue Advanced Education: Obtaining a master's degree or Ph.D. in a relevant field can open doors to higher-paying roles.
• Seek Leadership Roles: Transitioning into managerial or lead roles can significantly boost your earning potential.
• Negotiate Effectively: Regularly review your compensation package and negotiate for raises or better benefits based on your performance and market trends.
• Explore Opportunities in High-Paying Industries: Consider roles in industries known for higher compensation, such as finance or tech.

Educational Requirements

Most Data Infrastructure Engineer positions require at least a bachelor's degree in computer science, information technology, or a related field. However, many employers prefer candidates with a master's degree, especially for senior roles. A strong foundation in computer science principles, data management, and systems architecture is essential. Coursework in data structures, algorithms, database management, and distributed systems is particularly beneficial.

Helpful Certifications

While not always mandatory, certain certifications can enhance your qualifications and demonstrate your expertise to potential employers. Some valuable certifications include:

• AWS Certified Solutions Architect: Validates your ability to design and deploy scalable systems on AWS.
• Google Professional Data Engineer: Demonstrates proficiency in designing data processing systems and operationalizing machine learning models.
• Microsoft Certified: Azure Data Engineer Associate: Focuses on implementing data solutions using Azure services.
• Certified Kubernetes Administrator (CKA): Useful for roles involving container orchestration and management.

Required Experience

Typically, employers look for candidates with 3 to 5 years of experience in data engineering, software development, or IT infrastructure roles. Experience with cloud platforms, data warehousing solutions, and big data technologies is highly valued. Familiarity with programming languages such as Python, Java, or Scala, and tools like Apache Hadoop, Spark, or Kafka, is often required. Experience in designing and maintaining scalable data architectures is crucial.

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