Salary for Senior-level / Expert Data Infrastructure Engineer in United States during 2024

Salary details

The average senior-level / expert Data Infrastructure Engineer salary lies between USD 150,000 and USD 241,000 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: Dec. 22, 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 Engineering, Python and AWS. 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 | 35 jobs Python | 32 jobs AWS | 30 jobs Pipelines | 28 jobs Spark | 26 jobs Kafka | 23 jobs Security | 23 jobs Data pipelines | 23 jobs Kubernetes | 21 jobs Terraform | 21 jobs SQL | 20 jobs Big Data | 19 jobs Architecture | 18 jobs Computer Science | 18 jobs GCP | 17 jobs Java | 17 jobs Machine Learning | 15 jobs Airflow | 15 jobs CI/CD | 15 jobs Flink | 13 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 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 | 33 jobs Health care | 29 jobs Equity / stock options | 27 jobs Flex hours | 19 jobs Flex vacation | 19 jobs Startup environment | 18 jobs Insurance | 17 jobs Parental leave | 16 jobs Competitive pay | 13 jobs Team events | 12 jobs Salary bonus | 12 jobs Medical leave | 10 jobs Wellness | 8 jobs 401(k) matching | 5 jobs Relocation support | 5 jobs Fertility benefits | 5 jobs Home office stipend | 3 jobs Lunch / meals | 2 jobs Gear | 2 jobs Snacks / Drinks | 2 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Data Infrastructure Engineer can vary significantly based on region, industry, and company size. Typically, the salary is divided into three main components: base salary, bonuses, and additional remuneration such as stock options or benefits.

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation package. In tech hubs like San Francisco or New York, the base salary might be higher due to the cost of living and competitive job market.

• Bonuses: These can be performance-based or company-wide bonuses. Performance bonuses are tied to individual or team achievements, while company-wide bonuses depend on the overall success of the company. Bonuses can range from 10% to 20% of the base salary.

• Additional Remuneration: This includes stock options, restricted stock units (RSUs), and other benefits like health insurance, retirement plans, and paid time off. Tech companies, especially startups, often offer equity as a significant part of the compensation package.

Increasing Salary Further

To increase your salary beyond the median of USD 175,800, consider the following strategies:

• Specialize in High-Demand Skills: Focus on acquiring expertise in cutting-edge technologies or methodologies within AI/ML and data infrastructure, such as cloud computing, big data technologies, or machine learning frameworks.

• Leadership Roles: Transition into leadership or managerial roles, such as a Data Infrastructure Manager or Director, which typically offer higher compensation.

• Industry Shift: Consider moving to industries that pay higher salaries for data infrastructure roles, such as finance, healthcare, or tech giants.

• Geographic Relocation: Relocating to regions with higher demand and compensation for tech roles, like Silicon Valley or Seattle, can also lead to salary increases.

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 Ph.D. can be advantageous, especially for roles that require deep technical expertise or research capabilities. Advanced degrees can also provide a competitive edge and potentially lead to higher salaries.

Helpful Certifications

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

• Certified Data Management Professional (CDMP)
• AWS Certified Solutions Architect
• Google Professional Data Engineer
• Microsoft Certified: Azure Data Engineer Associate

These certifications validate your skills in managing and architecting data infrastructure on popular cloud platforms, which is highly valued by employers.

Required Experience

Typically, a Senior-level Data Infrastructure Engineer is expected to have at least 5-10 years of experience in data engineering, software development, or a related field. Experience with designing and implementing large-scale data systems, proficiency in programming languages like Python or Java, and familiarity with data processing frameworks such as Hadoop or Spark are often required.

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