A Data Integration Specialist is a proficient IT professional who designs, develops, and deploys data integration solutions, ensuring the seamless flow of information across multiple systems and platforms. They combine expertise in data management, ETL processes, and system interoperations.
Potential Lateral Jobs
Data Integration Specialist
$57,634 / year
The average salary for Data Integration Specialist is $57,634 / year according to Payscale.com
There are no updated reports for Data Integration Specialist salaries. You can check potential lateral job opportunities in this information stack to find related salary information.
Data Integration Specialist role may have an alternate title depending on the company. To find more information, you can check Payscale.com.
As a Data Integration Specialist, you will be responsible for designing and implementing data integration solutions for organizations. You will need a strong understanding of data integration technologies and tools, as well as experience with data modeling and ETL processes. Strong problem-solving and analytical skills are essential, as you will be responsible for ensuring data accuracy and availability.
The following text about the Job role of Data Integration Specialist has been generated by an AI model developed by Cohere. While efforts have been made to ensure the accuracy and coherence of the content, there is a possibility that the model may produce hallucinated or incorrect information. Therefore, we strongly recommend independently verifying any information provided in this text before making any decisions or taking any actions based on it.
The Data Integration Specialist is responsible for designing, developing, and maintaining data integration processes and systems. They work with a variety of data sources and targets, including databases, data warehouses, and cloud-based platforms. They must have a strong understanding of data architecture and data modeling, as well as experience with data integration tools and technologies.
The most important skills for a Data Integration Specialist include:
Strong understanding of data architecture and data modeling
Experience with data integration tools and technologies, such as Informatica, DataStage, or SSIS
Knowledge of data sources and targets, including databases, data warehouses, and cloud-based platforms
Strong problem-solving and analytical skills
Excellent communication and collaboration abilities
The Data Integration Specialist's primary responsibilities include:
Designing and developing data integration processes and systems
Working with a variety of data sources and targets, including databases, data warehouses, and cloud-based platforms
Creating data models and mapping data between sources and targets
Testing and debugging data integration processes
Maintaining and supporting data integration systems
Collaborating with cross-functional teams to ensure data integration needs are met
The Data Integration Specialist is a critical member of any team that relies on data to drive business decisions. They play a crucial role in ensuring that data is accurate, timely, and accessible to those who need it. With their strong understanding of data architecture and data modeling, as well as experience with data integration tools and technologies, they are well-equipped to design, develop, and maintain data integration processes and systems that can support the needs of the business.
Potential Lateral Jobs
Explore the wide range of potential lateral job opportunities and career paths that are available in this role.
Most roles require at least a bachelor's degree. To remain competitive, job seekers should consider specialization or skill-specific programs such as specialization, bootcamps or certifications.
Consider pursuing specialized certifications or vendor-specific programs to enhance your qualifications and stand out in the job market.
AWS Certified Database — Specialty
The AWS Database Certification — Specialty program is intended to validate candidates' expertise in recommending, designing, and implementing AWS cloud-based relational and NoSQL database systems.
The Google Certified Professional Data Engineer is a high-ROI program designed for experienced professionals to become highly equipped with specialty skills and functional knowledge in cloud data engineering.
The Databricks Data Engineer Certification program is highly sought after, designed to evaluate an individual's proficiency in utilizing the Databricks Lakehouse Platform for performing fundamental data engineering tasks.
Microsoft Certified: Azure Data Engineer Associate
The Microsoft Certified: Azure Data Engineer Associate program is designed for professionals who have expertise in integrating, transforming, and consolidating data from various structured, unstructured, and streaming data systems.
Google Certified Professional Cloud Database Engineer
The Google Certified Professional Cloud Database Engineer program is designed for experienced database engineers with a strong background in both Cloud computing and overall database and IT experience.
If you want to improve your skills and knowledge in a particular field, you should think about enrolling in a Nanodegree or specialization program. This can greatly improve your chances of finding a job and make you more competitive in the job market.
Google Cloud Certified Professional Data Engineer
The training program provides a comprehensive video course, practice tests, exam questions, and a free test to develop data engineering skills on Google Cloud Platform (GCP) and pass the certification exam.
This career track is designed for beginners to learn Python basics, build data architecture, streamline processing, and maintain large-scale systems. Participants will develop pipelines, automate tasks, and construct high-performance databases using Shell, SQL, and Scala.
This Nanodegree program teaches you how to access data silos, extract information from various sources, and streamline it into functional formats for analysts and high-level decision-makers. You will have the opportunity to create an impressive, machine learning-driven web application with significant real-world, life-saving implications.
You will acquire the skills to design data models, create data pipelines, and navigate large datasets on the Azure platform. Additionally, you will learn to build data warehouses, data lakes, and lakehouse architecture.
We are soon crowdsourcing these resource stacks to collate the best resources, such as publications, community groups, job boards, etc., that are practically suitable for every contextual stack.
Discover the wide array of publications that professionals in this role actively engage with, expanding their knowledge and staying informed about the latest industry trends and developments.
Discover the thriving communities where professionals in this role come together to exchange knowledge, foster collaboration, and stay at the forefront of industry trends.
We are currently in the process of updating contextual resources and we will be adding the new ones to the list shortly.
AI Disclosure: We are testing AI technologies to ensure the accuracy and coherence of recommendations. However, it is important to note that there is a possibility that the model may create hallucinated or incorrect inferences. Therefore, we highly recommend independently verifying any information provided in these stacks before making any decisions or taking any actions based on it.
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