Salary for Senior-level / Expert DataOps Engineer during 2024

Salary details

The average senior-level / expert DataOps Engineer salary lies between USD 73,008 and USD 170,640 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 Senior-level / Expert DataOps Engineer roles

The three most common job tag items assiciated with senior-level / expert DataOps Engineer job listings are DataOps, 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:

DataOps | 37 jobs Python | 32 jobs Pipelines | 29 jobs SQL | 26 jobs Engineering | 25 jobs Terraform | 25 jobs Security | 24 jobs AWS | 23 jobs Data pipelines | 23 jobs DevOps | 22 jobs Kubernetes | 19 jobs CI/CD | 19 jobs Snowflake | 14 jobs ETL | 13 jobs Kafka | 13 jobs Airflow | 13 jobs Architecture | 13 jobs Computer Science | 13 jobs Data quality | 13 jobs PostgreSQL | 12 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert DataOps Engineer job listings are Career development, Flex hours and Team events. 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 | 22 jobs Flex hours | 13 jobs Team events | 13 jobs Health care | 11 jobs Parental leave | 10 jobs Startup environment | 10 jobs Equity / stock options | 9 jobs Salary bonus | 8 jobs Competitive pay | 7 jobs Insurance | 6 jobs Flex vacation | 5 jobs Medical leave | 5 jobs Gear | 4 jobs Transparency | 2 jobs Home office stipend | 2 jobs Paid sabbatical | 2 jobs 401(k) matching | 1 jobs Fitness / gym | 1 jobs Signing bonus | 1 jobs Relocation support | 1 jobs

Salary Composition

The salary for a Senior-level or Expert DataOps Engineer typically comprises a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Bonuses can be performance-based or company-wide and may vary significantly depending on the company's financial health and individual performance. Additional remuneration might include stock options, especially in tech companies, and benefits like health insurance, retirement plans, and paid time off.

Regional differences play a significant role; for instance, salaries in tech hubs like San Francisco or New York are generally higher due to the cost of living and demand for talent. Industry also impacts salary composition, with finance and tech sectors often offering more lucrative packages. Company size can influence the structure as well; larger companies might offer more comprehensive benefits, while startups might compensate with equity options.

Increasing Salary

To increase your salary from a Senior-level DataOps Engineer position, consider the following strategies:

• Skill Enhancement: Continuously update your skills with the latest technologies and methodologies in AI/ML and DataOps. Specializing in niche areas can make you more valuable.
• Leadership Roles: Transition into leadership or managerial roles, such as a DataOps Manager or Director, which typically offer higher salaries.
• Industry Change: Moving to a higher-paying industry, such as finance or healthcare, can result in a salary increase.
• Negotiation: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry salary standards.

Educational Requirements

Most Senior-level DataOps Engineer positions require at least a bachelor's degree in computer science, data science, engineering, or a related field. However, a master's degree or even a Ph.D. can be advantageous, especially for roles that require deep technical expertise or research capabilities. Advanced degrees can also provide a competitive edge in salary negotiations and career advancement.

Helpful Certifications

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

• Certified Data Management Professional (CDMP)
• AWS Certified Big Data – Specialty
• Google Professional Data Engineer
• Microsoft Certified: Azure Data Engineer Associate
• Certified Kubernetes Administrator (CKA)

These certifications can validate your skills in specific tools and platforms, making you more attractive to potential employers.

Required Experience

Typically, a Senior-level DataOps Engineer is expected to have 5-10 years of experience in data engineering, data management, or related fields. This experience should include a strong background in data architecture, cloud platforms, and automation tools. Experience in leading projects, mentoring junior engineers, and collaborating with cross-functional teams is also highly valued.

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