Salary for Executive-level / Director Platform Engineer during 2024

Salary details

The average executive-level / director Platform Engineer salary lies between USD 145,000 and USD 214,500 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: Dec. 22, 2024

Top 20 Job Tags for Executive-level / Director Platform Engineer roles

The three most common job tag items assiciated with executive-level / director Platform Engineer job listings are Engineering, Architecture and Kubernetes. 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 | 24 jobs Architecture | 16 jobs Kubernetes | 13 jobs Security | 13 jobs Agile | 13 jobs Computer Science | 13 jobs Testing | 12 jobs Azure | 12 jobs Python | 11 jobs Machine Learning | 11 jobs AWS | 11 jobs CI/CD | 10 jobs Finance | 9 jobs Pipelines | 8 jobs LLMs | 8 jobs Java | 8 jobs Generative AI | 8 jobs MLOps | 7 jobs Scala | 6 jobs CX | 6 jobs

Top 20 Job Perks/Benefits for Executive-level / Director Platform Engineer roles

The three most common job benefits and perks assiciated with executive-level / director Platform Engineer job listings are Career development, Health care and Startup environment. 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 | 25 jobs Health care | 15 jobs Startup environment | 11 jobs Competitive pay | 11 jobs Insurance | 9 jobs Salary bonus | 8 jobs Equity / stock options | 7 jobs Flex hours | 6 jobs Flex vacation | 6 jobs Medical leave | 6 jobs Team events | 5 jobs Wellness | 4 jobs Transparency | 3 jobs 401(k) matching | 2 jobs Parental leave | 2 jobs Home office stipend | 1 jobs Flexible spending account | 1 jobs

Salary Composition

The salary for an Executive-level or Director Platform Engineer in AI/ML/Data Science typically comprises several components. The fixed base salary is the largest portion, often accounting for 60-80% of the total compensation package. Bonuses, which can be performance-based or tied to company profits, usually make up 10-20%. Additional remuneration might include stock options, especially in tech companies or startups, and other benefits like health insurance, retirement contributions, and paid time off. The exact composition can vary significantly depending on the region, industry, and company size. For instance, tech hubs like Silicon Valley might offer higher base salaries and more substantial stock options, while companies in other regions might focus more on bonuses and benefits.

Increasing Salary Further

To increase your salary beyond the median of USD 170,250, consider pursuing roles with greater responsibility, such as VP of Engineering or Chief Technology Officer (CTO). Expanding your skill set to include emerging technologies and leadership capabilities can also be beneficial. Networking within the industry and building a strong personal brand can open doors to higher-paying opportunities. Additionally, negotiating your salary based on market research and your proven track record can lead to better compensation packages.

Educational Requirements

Most executive-level positions in AI/ML/Data Science require at least a bachelor's degree in computer science, engineering, mathematics, or a related field. However, a master's degree or Ph.D. is often preferred, especially for roles that involve significant technical oversight or research. Advanced degrees can provide a deeper understanding of complex algorithms and data structures, which are crucial for high-level decision-making in AI/ML projects.

Helpful Certifications

While not always mandatory, certain certifications can enhance your qualifications and demonstrate your expertise. Certifications such as Certified Data Scientist (CDS), Google Professional Machine Learning Engineer, and AWS Certified Machine Learning – Specialty are highly regarded. These certifications validate your skills in specific platforms and tools, which can be advantageous in a competitive job market.

Required Experience

Typically, a minimum of 10-15 years of experience in software engineering, data science, or a related field is required for an executive-level position. This experience should include a proven track record of leading teams, managing large-scale projects, and delivering successful AI/ML solutions. Experience in strategic planning and cross-functional collaboration is also crucial, as these roles often involve working closely with other departments to align technology initiatives with business goals.

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