Original listing text, shown exactly as published by the company.
Responsibilities
- Design, develop, test, deploy, and monitor scalable applications for data ingestion, mastering, matching, and publishing
- Develop high-quality software using Java and Python, ensuring performance, maintainability, extensibility, and reliability.
- Deliver end-to-end features across the software stack, operating with ownership of assigned components.
- Build and maintain microservices and REST APIs, including real-time and streaming data capabilities.
- Collaborate with solution architects and partner with lead architects to contribute to system design, reference architectures, and baseline implementations.
- Contribute to platform modernization by simplifying, harmonizing, and optimizing systems to improve scalability and performance.
- Validate solutions through proofs of concept and prototyping prior to full implementation.
- Develop and optimize large-scale distributed data systems using modern frameworks (e.g., Spark, Hadoop, distributed processing technologies).
- Collaborate with Data Science teams to implement advanced algorithms, models, and proprietary capabilities into production systems.
- Ensure high availability, resilience, and performance of critical data processing systems (e.g., identity resolution/Match platforms).
- Work cross-functionally with business stakeholders, QA, DevOps, and product teams to align technical solutions with business objectives.
- Ensure code quality through testing, peer reviews, and adherence to development standards.
- Contribute to CI/CD pipelines, automation, and modern engineering practices.
- Troubleshoot and resolve complex production issues using strong root cause analysis skills.
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Ensure compliance with data governance, information security, and regulatory standards.
Essential Skills and/or certifications
- Bachelor’s degree in Computer Science or related areas
- At least 5 years of experience developing commercial software
- Strong proficiency in Java and Python with solid object-oriented design principles
- Experience building large-scale distributed systems and data platforms
- Expertise in big data frameworks (e.g., Hadoop, Spark, EMR, Dataproc)
- Advanced SQL and data modeling knowledge
- Experience developing cloud-native solutions (AWS, GCP, or equivalent)
- Experience with CI/CD pipelines, automated testing frameworks, and monitoring tools
- Knowledge of microservices architecture and high-availability systems
- Strong problem-solving and root cause analysis capabilities
- Ability to work independently while collaborating in cross-functional teams
- Strong communication and stakeholder management skills
- Proficiency in Microsoft Office Suite skills
- Show an ownership mindset in everything you do. Be a problem solver, be curious and be inspired to take action. Be proactive, seek ways to collaborate and connect with people and teams in support of driving success.
- Continuous growth mindset, keep learning through social experiences and relationships with stakeholders, experts, colleagues and mentors as well as widen and broaden your competencies through structural courses and programs.
- Where applicable, fluency in English and languages relevant to the working market.
