Back to SearchSenior Data Integration Engineer
Data Integration
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We are looking for a highly skilled Senior Data Integration Engineer to take a leading role in designing and refining data integration processes.
You will collaborate with various teams to build efficient workflows that seamlessly connect systems and drive business success. This role provides an excellent opportunity to work on impactful projects in a dynamic and forward-thinking environment.
Responsibilities
- Build and deploy effective data integration solutions that align with organizational priorities
- Collaborate with different teams to gather requirements and develop integration plans
- Analyze, troubleshoot, and improve data workflows to ensure optimal performance and reliability
- Create and maintain detailed documentation for integration workflows and system designs
- Uphold data security and ensure adherence to relevant compliance standards
- Conduct code reviews and provide feedback to enhance team performance
- Stay current with emerging technologies and trends in data integration
- Contribute to the evolution of tools, processes, and practices to boost efficiency
Requirements
- A Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related discipline
- At least 3 years of hands-on experience in data integration or a related field
- In-depth knowledge of SDLC methodologies and their practical application
- Proven experience in implementing SDLC processes in real-world scenarios
- Familiarity with Agile principles and their use in development workflows
- Advanced skills in SQL for database management and querying
- Experience working with NoSQL database systems
- Proficiency with CI/CD tools and experience in pipeline configuration
- Strong command of English, both written and verbal, at a B2+ level or higher
Nice to have
- Experience with cloud platforms such as AWS, Google Cloud, or Azure
- Hands-on expertise with ETL tools for data migration and transformation
- Understanding of API development and integration techniques
- Exposure to big data ecosystems like Spark or Hadoop
- Certifications in relevant areas such as data engineering or cloud technologies