Strong analytical, problem-solving, and debugging skills.
Preferred Skills
Experience with Databricks (highly desirable).
Exposure to cloud platforms and modern data engineering practices.
Experience with CI/CD pipelines, Git, and Agile development methodologies.
Knowledge of regulatory reporting or financial services domain is a plus.
AI Mindset & Engineering Excellence
Demonstrated ability and willingness to adopt AI-assisted development tools (e.g., GitHub Copilot, Devin, Databricks Assistant, or similar) to improve productivity, code quality, and delivery efficiency.
Ability to effectively leverage AI-generated recommendations for coding, testing, debugging, documentation, and analysis while maintaining accountability for final deliverables.
Strong engineering judgment to critically review, validate, and optimize AI-generated code and solutions rather than relying solely on tool outputs.
Capable of identifying potential functional, performance, security, and maintainability issues in AI-assisted implementations and making appropriate corrections.
Passion for continuous learning and staying current with emerging AI technologies and software engineering best practices.
Nice to Have
Experience with Spark performance tuning.
Familiarity with data lake architectures.
Experience leveraging AI tools such as Copilot or similar developer productivity solutions.
This role offers an opportunity to work on large-scale data platforms, modernization initiatives, and business-critical applications while collaborating with global team
We are seeking an Intermediate Big Data Spark Developer to design, develop, enhance, and support large-scale data processing solutions.
The ideal candidate is a strong Spark developer with proficiency in Java or Python, a solid understanding of distributed data processing, and a growth mindset toward adopting modern AI-powered development practices. They should be able to combine the productivity gains offered by AI tools with sound technical judgment, ensuring solutions are accurate, scalable, maintainable, and production-ready.
Key Responsibilities
Design, develop, test, and maintain data processing applications using Apache Spark.
Build scalable ETL and data transformation pipelines for large datasets.
Develop and support applications using Java or Python in a distributed data environment.
Analyze requirements and collaborate with business analysts, QA teams, and stakeholders to deliver solutions.
Troubleshoot production issues and optimize application performance.
Participate in code reviews and follow engineering best practices.
Contribute to application modernization, migration, and automation initiatives.
Leverage AI-assisted development tools to improve productivity and quality.
Required Skills
8-10 years of software development experience.
Strong hands-on experience with Apache Spark.
Proficiency in either Java or Python.
Candidates with primary expertise in Python should have a good understanding of Java fundamentals (OOP concepts, collections, exception handling, multithreading basics).
Experience working with SQL and relational databases.
Understanding of distributed computing concepts and big data processing.
Strong analytical, problem-solving, and debugging skills.
Preferred Skills
Experience with Databricks (highly desirable).
Exposure to cloud platforms and modern data engineering practices.
Experience with CI/CD pipelines, Git, and Agile development methodologies.
Knowledge of regulatory reporting or financial services domain is a plus.
AI Mindset & Engineering Excellence
Demonstrated ability and willingness to adopt AI-assisted development tools (e.g., GitHub Copilot, Devin, Databricks Assistant, or similar) to improve productivity, code quality, and delivery efficiency.
Ability to effectively leverage AI-generated recommendations for coding, testing, debugging, documentation, and analysis while maintaining accountability for final deliverables.
Strong engineering judgment to critically review, validate, and optimize AI-generated code and solutions rather than relying solely on tool outputs.
Capable of identifying potential functional, performance, security, and maintainability issues in AI-assisted implementations and making appropriate corrections.
Passion for continuous learning and staying current with emerging AI technologies and software engineering best practices.
Nice to Have
Experience with Spark performance tuning.
Familiarity with data lake architectures.
Experience leveraging AI tools such as Copilot or similar developer productivity solutions.
This role offers an opportunity to work on large-scale data platforms, modernization initiatives, and business-critical applications while collaborating with global team
Job Family Group
Technology
Job Family
Applications Development
Time Type
Full time
- Most Relevant Skills
- Please see the requirements listed above.
- Other Relevant Skills
- For complementary skills, please see above and/or contact the recruiter.
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