Data Integration Engineer

About the role

NXP is looking for a Data Integration Engineer in Bangalore to act as a Senior Data Engineer and help design, develop and maintain integration solutions that connect business applications and systems. The role translates functional requirements into technical solutions that follow NXP's process, architecture, design and security guidelines.

Key responsibilities

• Design, develop and maintain complex data integration solutions ensuring seamless data flow across systems and platforms.
• Lead the design and implementation of integration solutions, ensuring data accuracy, integrity and security.
• Optimize data integration processes, including data mapping, transformation and orchestration.
• Transform and load data from multiple sources into the data warehouse, keeping it consistent and reliable.
• Work with business analysts, developers and stakeholders to understand requirements and deliver solutions.
• Deploy solutions continuously using CI/CD processes and tools such as GitLab.
• Maintain documentation of integration processes, data mappings and system configurations.
• Ensure compliance with industry standards and regulations on data exchange and security.
• Mentor junior data engineers.

Required profile

• Bachelor's or Master's degree in Computer Science, Information Technology or equivalent years of relevant experience.
• 5-8 years of experience in data engineering, focused on data integration.
• Deep expertise in TIBCO BusinessWorks 5 and 6, Container Edition, or Snaplogic/Workato.
• Experience with messaging solutions such as TIBCO EMS and RV, or open-source options like Kafka or Pulsar.
• Ability to work with a geographically dispersed, multi-cultural team and to collaborate with business and IT on changes.

Required skills

• Strong SQL, Python and data transformation tools; knowledge of XML, XSLT, XSD, WSDL, SOAP and REST APIs.
• SAP and SAP ALE (IDoc).
• Cloud-based data integration platforms such as AWS and Azure.
• API integration, web services, data governance and data quality best practices.
• Preferred: Java, JavaScript, UML, Git, relational databases, HTML, CSS, XPath, SOA and microservices.