Salary for Senior-level / Expert Data Infrastructure Engineer during 2023

Salary details

The average senior-level / expert Data Infrastructure Engineer salary lies between USD 145,000 and USD 200,000 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 Senior-level / Expert Data Infrastructure Engineer roles

The three most common job tag items assiciated with senior-level / expert Data Infrastructure Engineer job listings are Python, AWS and Kafka. 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:

Python | 20 jobs AWS | 18 jobs Kafka | 16 jobs Engineering | 15 jobs Pipelines | 15 jobs Spark | 14 jobs SQL | 14 jobs Kubernetes | 14 jobs Machine Learning | 13 jobs Architecture | 13 jobs Terraform | 13 jobs Data pipelines | 12 jobs GCP | 12 jobs Java | 12 jobs Data warehouse | 11 jobs Privacy | 11 jobs Azure | 10 jobs Snowflake | 10 jobs BigQuery | 9 jobs Streaming | 9 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Data Infrastructure Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert Data Infrastructure Engineer job listings are Health care, Career development and Startup environment. 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:

Health care | 14 jobs Career development | 11 jobs Startup environment | 10 jobs Flex hours | 9 jobs Equity / stock options | 8 jobs Parental leave | 7 jobs Flex vacation | 7 jobs Medical leave | 6 jobs Insurance | 6 jobs 401(k) matching | 4 jobs Gear | 4 jobs Home office stipend | 4 jobs Team events | 3 jobs Salary bonus | 3 jobs Unlimited paid time off | 3 jobs Wellness | 2 jobs Competitive pay | 2 jobs Signing bonus | 2 jobs Relocation support | 1 jobs Fertility benefits | 1 jobs

Salary Composition

The salary for a Senior-level or Expert Data Infrastructure Engineer typically comprises several components: 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 and industry, ranging from 10-20% of the base salary. In tech hubs like Silicon Valley, equity or stock options can be a substantial part of the compensation, sometimes making up 20-30% of the total package. In regions with a high cost of living, such as New York or San Francisco, salaries tend to be higher to offset living expenses. Similarly, larger companies or those in high-demand industries like finance or technology may offer more competitive compensation packages.

Increasing Salary

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

• Specialization: Develop expertise in niche areas of data infrastructure, such as cloud computing, big data technologies, or machine learning infrastructure, which are in high demand.
• Leadership Roles: Transition into leadership or managerial roles, such as a Data Infrastructure Manager or Director, which typically offer higher salaries.
• Continuous Learning: Stay updated with the latest technologies and trends in data infrastructure to remain competitive and valuable to employers.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation during job offers or performance reviews.

Educational Requirements

Most Senior-level Data Infrastructure Engineer positions require at least a bachelor's degree in computer science, information technology, or a related field. However, a master's degree or even a Ph.D. can be advantageous, especially for roles in research-intensive industries or companies. Advanced degrees can provide a deeper understanding of complex data systems and algorithms, which is beneficial for tackling sophisticated infrastructure challenges.

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 Solutions Architect Expert: Confirms your skills in designing and implementing solutions on Microsoft Azure.
• Certified Kubernetes Administrator (CKA): Shows your capability in managing Kubernetes clusters, which are crucial for modern data infrastructure.

Required Experience

Typically, a Senior-level Data Infrastructure Engineer is expected to have 5-10 years of experience in data engineering, software development, or IT infrastructure roles. This experience should include hands-on work with data pipelines, cloud platforms, and large-scale data processing systems. Experience in leading projects or teams is also highly valued, as it demonstrates your ability to manage complex tasks and collaborate effectively with cross-functional teams.

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