Salary for Senior-level / Expert Data Integration Developer in United States during 2024

Salary details

The average senior-level / expert Data Integration Developer salary lies between USD 105,267 and USD 173,689 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: Nov. 17, 2024

Top 20 Job Tags for Senior-level / Expert Data Integration Developer roles

The three most common job tag items assiciated with senior-level / expert Data Integration Developer job listings are ETL, SQL and SDLC. 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:

ETL | 16 jobs SQL | 13 jobs SDLC | 12 jobs Security | 11 jobs Computer Science | 11 jobs Data Warehousing | 10 jobs Architecture | 10 jobs Data quality | 9 jobs Engineering | 8 jobs Data pipelines | 8 jobs Snowflake | 8 jobs Pipelines | 8 jobs Data management | 8 jobs Mathematics | 8 jobs Data warehouse | 8 jobs Oracle | 7 jobs Talend | 7 jobs Informatica | 7 jobs Jira | 7 jobs CI/CD | 7 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Data Integration Developer roles

The three most common job benefits and perks assiciated with senior-level / expert Data Integration Developer job listings are Health care, Career development and Wellness. 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:

Health care | 8 jobs Career development | 8 jobs Wellness | 6 jobs Team events | 2 jobs Flex hours | 1 jobs Competitive pay | 1 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Data Integration Developer in AI/ML/Data Science typically includes a combination of a fixed base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. The base salary often constitutes the majority of the total compensation package, usually ranging from 70% to 85%. Performance bonuses can vary significantly depending on the company and industry, often ranging from 10% to 20% of the total compensation. Additional remuneration, such as stock options or profit-sharing, is more common in larger tech companies or startups and can account for 5% to 15% of the total package. Regional differences also play a role, with tech hubs like Silicon Valley, New York, and Seattle offering higher compensation packages compared to other regions.

Increasing Salary

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

• Specialize in Niche Areas: Developing expertise in niche areas of AI/ML, such as natural language processing, computer vision, or reinforcement learning, can make you more valuable and justify a higher salary.
• Leadership Roles: Transitioning into leadership roles, such as a team lead or manager, can significantly increase your earning potential.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML and data science. This can involve taking advanced courses, attending workshops, or obtaining additional certifications.
• Networking: Building a strong professional network can open up opportunities for higher-paying positions and collaborations.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation during job offers or performance reviews.

Educational Requirements

Most Senior-level or Expert Data Integration Developer roles in AI/ML/Data Science require at least a bachelor's degree in computer science, data science, mathematics, statistics, or a related field. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex problem-solving and advanced algorithm development. These advanced degrees provide a deeper understanding of theoretical concepts and practical applications, which are crucial for high-level positions.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise to potential employers. Some common and beneficial certifications include:

• Certified Data Scientist (CDS)
• Microsoft Certified: Azure Data Scientist Associate
• Google Professional Data Engineer
• AWS Certified Machine Learning – Specialty
• Cloudera Certified Data Scientist (CCDS)

These certifications can validate your skills in specific tools and platforms, making you more competitive in the job market.

Required Experience

Typically, a Senior-level or Expert Data Integration Developer role requires a minimum of 5 to 10 years of experience in data integration, data engineering, or related fields. This experience should include hands-on work with data integration tools, ETL processes, and data warehousing. Experience in AI/ML projects, including model development and deployment, is also highly valued. Additionally, experience in leading projects or teams can be a significant advantage.

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