Data Infrastructure Engineer Salary in 2023

Salary details

The average Data Infrastructure Engineer salary lies between USD 151,090 and USD 190,000 globally. 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.

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 AWS, Python and Pipelines. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

AWS | 27 jobs Python | 26 jobs Pipelines | 24 jobs Engineering | 23 jobs SQL | 21 jobs Kafka | 20 jobs Architecture | 19 jobs Terraform | 19 jobs Spark | 18 jobs Machine Learning | 17 jobs Kubernetes | 17 jobs GCP | 17 jobs Privacy | 15 jobs Security | 14 jobs Data pipelines | 14 jobs Java | 14 jobs Data warehouse | 13 jobs Azure | 12 jobs NoSQL | 11 jobs Snowflake | 11 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 2023 and the number of open jobs that where offering them during that period:

Career development | 20 jobs Health care | 15 jobs Equity / stock options | 13 jobs Startup environment | 13 jobs Flex hours | 10 jobs Parental leave | 9 jobs Flex vacation | 8 jobs Competitive pay | 7 jobs Team events | 7 jobs Medical leave | 7 jobs Insurance | 6 jobs Unlimited paid time off | 6 jobs Gear | 5 jobs 401(k) matching | 4 jobs Home office stipend | 4 jobs Wellness | 3 jobs Salary bonus | 3 jobs Signing bonus | 2 jobs Relocation support | 1 jobs Fertility benefits | 1 jobs

Salary Composition

The salary for a Data Infrastructure Engineer in AI/ML/Data Science typically comprises a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The fixed base salary is the largest component, often accounting for 70-80% of the total compensation package. Bonuses can vary significantly depending on the company's performance and individual contributions, usually ranging from 10-20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can significantly increase the total compensation, especially if the company performs well. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York tend to be higher due to the cost of living and competitive job market. Industry-wise, tech companies generally offer higher salaries compared to other sectors like finance or healthcare.

Steps to Increase Salary

To increase your salary from the current position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools relevant to data infrastructure, such as cloud computing, big data technologies, and machine learning frameworks.
• Advanced Education: Pursuing a master's degree or specialized certifications can make you more competitive and justify a higher salary.
• Leadership Roles: Transitioning into a leadership or managerial role can significantly boost your earning potential.
• Networking: Building a strong professional network can open up opportunities for higher-paying positions.
• Negotiation Skills: Improve your negotiation skills to better advocate for salary increases during performance reviews or when switching jobs.

Educational Requirements

Most Data Infrastructure Engineer positions require at least a bachelor's degree in computer science, information technology, or a related field. A strong foundation in mathematics and statistics is also beneficial. Some employers may prefer candidates with a master's degree, especially for more senior roles. Courses in data management, database systems, and software engineering are particularly relevant.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate expertise:

• 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 Data Management Professional (CDMP): Offers a broad understanding of data management principles.

Required Experience

Typically, a Data Infrastructure Engineer role requires 3-5 years of experience in related fields such as software engineering, database management, or IT infrastructure. Experience with cloud platforms, big data technologies, and data warehousing solutions is often essential. For senior positions, 5-10 years of experience with a proven track record of managing complex data infrastructure projects is common.

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