Salary for Mid-level / Intermediate Data Integration Engineer in United States during 2024

Salary details

The average mid-level / intermediate Data Integration Engineer salary lies between USD 86,700 and USD 130,000 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: Nov. 17, 2024

Top 20 Job Tags for Mid-level / Intermediate Data Integration Engineer roles

The three most common job tag items assiciated with mid-level / intermediate Data Integration Engineer job listings are SQL, Engineering and Python. 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:

SQL | 31 jobs Engineering | 29 jobs Python | 21 jobs Computer Science | 21 jobs ETL | 16 jobs APIs | 13 jobs Security | 12 jobs Architecture | 11 jobs Azure | 11 jobs AWS | 10 jobs Pipelines | 10 jobs JSON | 9 jobs Testing | 9 jobs Agile | 9 jobs XML | 9 jobs Business Intelligence | 8 jobs Consulting | 8 jobs Data pipelines | 8 jobs Data analysis | 8 jobs Oracle | 7 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Data Integration Engineer roles

The three most common job benefits and perks assiciated with mid-level / intermediate Data Integration Engineer job listings are Career development, Health care and Flex hours. 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 | 17 jobs Health care | 14 jobs Flex hours | 9 jobs Flex vacation | 9 jobs Startup environment | 9 jobs Equity / stock options | 8 jobs Insurance | 7 jobs Team events | 6 jobs Wellness | 5 jobs Competitive pay | 5 jobs Home office stipend | 5 jobs Snacks / Drinks | 4 jobs Salary bonus | 4 jobs Parental leave | 3 jobs Yoga | 3 jobs Medical leave | 2 jobs Flat hierarchy | 1 jobs Relocation support | 1 jobs

Salary Composition

The salary for a Mid-level Data Integration Engineer in the United States typically comprises a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually forms the majority of the total compensation package. Bonuses can vary significantly depending on the company's performance, individual performance, and industry standards. In tech-heavy regions like Silicon Valley, bonuses and stock options might be more substantial compared to other areas. Additionally, larger companies or those in high-demand industries like finance or technology may offer more competitive compensation packages, including comprehensive benefits such as health insurance, retirement plans, and professional development opportunities.

Steps to Increase Salary

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

• Skill Enhancement: Continuously update your skills in emerging technologies and tools relevant to AI/ML and data science. Proficiency in programming languages like Python, R, and SQL, as well as experience with data integration tools, can be advantageous.
• Advanced Education: Pursuing a master's degree or specialized certifications in data science or machine learning can make you more competitive.
• Networking: Engage with professional networks and communities to learn about new opportunities and trends in the industry.
• Leadership Roles: Seek opportunities to lead projects or teams, which can demonstrate your capability for higher responsibility roles.
• Industry Transition: Consider moving to industries that offer higher pay scales for data integration roles, such as finance or healthcare.

Educational Requirements

Most mid-level data integration engineer positions require at least a bachelor's degree in computer science, information technology, data science, or a related field. Some employers may prefer candidates with a master's degree, especially for roles that involve complex data integration tasks or require a deep understanding of machine learning algorithms.

Helpful Certifications

Certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:

• Certified Data Management Professional (CDMP)
• Microsoft Certified: Azure Data Engineer Associate
• Google Professional Data Engineer
• AWS Certified Data Analytics – Specialty
• IBM Data Science Professional Certificate

These certifications can validate your skills in data integration, cloud platforms, and data analytics, making you a more attractive candidate.

Required Experience

Typically, a mid-level data integration engineer is expected to have 3-5 years of experience in data engineering, data integration, or a related field. Experience with data integration tools such as Informatica, Talend, or Apache Nifi, as well as familiarity with ETL processes, is often required. Additionally, experience working with large datasets and cloud platforms like AWS, Azure, or Google Cloud can be beneficial.

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