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

Salary details

The average mid-level / intermediate Data Integration Specialist salary lies between USD 77,040 and USD 105,000 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

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

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

Python | 17 jobs SQL | 16 jobs APIs | 15 jobs Research | 13 jobs Engineering | 12 jobs ETL | 10 jobs Data management | 10 jobs Unstructured data | 9 jobs Computer Science | 9 jobs AWS | 7 jobs Testing | 7 jobs Architecture | 7 jobs Excel | 7 jobs Data quality | 7 jobs Consulting | 6 jobs Security | 6 jobs Azure | 6 jobs Agile | 6 jobs Pipelines | 6 jobs Data Warehousing | 5 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Data Integration Specialist job listings are Career development, Health care and Competitive pay. 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 | 13 jobs Health care | 12 jobs Competitive pay | 8 jobs Insurance | 5 jobs Flex hours | 4 jobs Team events | 4 jobs 401(k) matching | 3 jobs Equity / stock options | 3 jobs Flex vacation | 3 jobs Wellness | 3 jobs Startup environment | 3 jobs Medical leave | 3 jobs Salary bonus | 2 jobs Parental leave | 1 jobs Fitness / gym | 1 jobs Relocation support | 1 jobs Snacks / Drinks | 1 jobs Yoga | 1 jobs Flexible spending account | 1 jobs

Salary Composition for a Mid-level Data Integration Specialist

The salary for a Mid-level Data Integration Specialist in the United States typically comprises a base salary, performance 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. Performance bonuses can vary significantly depending on the company’s policy and individual performance, often ranging from 5% to 15% of the base salary. Additional remuneration might include stock options, especially in tech companies, and comprehensive benefits packages that cover health insurance, retirement plans, and other perks.

Regional differences can affect salary composition, with tech hubs like San Francisco, New York, and Seattle offering higher base salaries and more lucrative stock options. Industry also plays a role; for instance, finance and tech industries tend to offer higher bonuses compared to healthcare or education sectors. Company size can influence the compensation structure as well, with larger companies often providing more substantial bonuses and stock options compared to smaller firms.

Steps to Increase Salary from This Position

To increase your salary from a Mid-level Data Integration Specialist position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools relevant to data integration, such as cloud platforms, machine learning, and big data technologies.
• Advanced Certifications: Obtain advanced certifications in data science, machine learning, or cloud computing to enhance your qualifications and bargaining power.
• Networking: Build a strong professional network by attending industry conferences, joining relevant professional groups, and engaging in online forums.
• Performance Excellence: Consistently exceed performance expectations and take on challenging projects that demonstrate your value to the organization.
• Negotiation: Be prepared to negotiate your salary during performance reviews or when offered a new position, using market data to support your case.

Educational Requirements

Most Mid-level Data Integration Specialist positions require at least a bachelor’s degree in a related field such as computer science, information technology, data science, or engineering. Some employers may prefer candidates with a master’s degree, especially for roles that involve complex data integration tasks or leadership responsibilities. A strong foundation in mathematics, statistics, and programming is essential, as these skills are critical for data integration tasks.

Helpful Certifications

Several certifications can be beneficial for a Data Integration Specialist, including:

• Certified Data Management Professional (CDMP): Offers a comprehensive understanding of data management principles.
• Microsoft Certified: Azure Data Engineer Associate: Validates skills in designing and implementing data solutions on Microsoft Azure.
• AWS Certified Data Analytics – Specialty: Demonstrates expertise in using AWS data lakes and analytics services.
• Google Professional Data Engineer: Focuses on designing, building, and operationalizing data processing systems on Google Cloud Platform.

These certifications can enhance your credibility and demonstrate your commitment to professional development.

Experience Requirements

Typically, a Mid-level Data Integration Specialist is expected to have 3 to 5 years of experience in data integration, data engineering, or a related field. Experience with data integration tools such as Informatica, Talend, or Apache Nifi, as well as proficiency in SQL and programming languages like Python or Java, is often required. Experience with cloud platforms (AWS, Azure, Google Cloud) and familiarity with ETL processes are also highly valued.

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