Big Data Software Engineer - Python

Location: Ciudad Autónoma de Buenos Aires, Argentina

Job Family: Software Engineering

About the Role

At JP Morgan Chase, we are a leading global financial services firm committed to innovation in banking, investment, and asset management. As a Big Data Software Engineer - Python in our Buenos Aires technology hub, you will play a pivotal role in building and enhancing large-scale data processing platforms that power our financial operations. This position involves leveraging Python to implement robust, cloud-based solutions for handling vast volumes of internal transaction data and third-party market feeds, ensuring seamless integration into our enterprise systems. You will contribute to initiatives that drive data-driven decision-making, risk assessment, and customer insights in the dynamic financial services landscape. Your day-to-day responsibilities will include designing scalable data pipelines, optimizing cloud infrastructures for efficiency, and collaborating with data scientists, analysts, and business leaders to deliver high-impact solutions. In this role, you will tackle challenges unique to the financial industry, such as real-time fraud detection, regulatory reporting, and portfolio analytics, while adhering to strict compliance standards. Working within an agile team, you will utilize cutting-edge technologies to process petabyte-scale datasets, fostering innovation that supports JP Morgan Chase's mission to enable economic growth worldwide. We seek engineers who thrive in a fast-paced environment and are passionate about transforming complex data into actionable intelligence. This opportunity offers exposure to global projects and the chance to grow within one of the world's most respected financial institutions. Join us in Buenos Aires to advance your career while contributing to the technological backbone of modern finance.

Key Responsibilities

• Design, develop, and maintain big data processing pipelines using Python on cloud platforms to handle internal and third-party financial datasets
• Collaborate with cross-functional teams to integrate large-scale data solutions into JP Morgan Chase's core banking systems
• Implement scalable algorithms for data ingestion, transformation, and analysis to support financial analytics and reporting
• Ensure data security, privacy, and compliance with regulations like GDPR and SOX in all processing activities
• Optimize cloud-based infrastructures for cost-efficiency and performance in handling terabyte-scale financial data
• Troubleshoot and resolve issues in production environments to maintain high availability of data services
• Contribute to the evolution of JP Morgan's big data ecosystem by adopting emerging technologies and best practices
• Participate in code reviews, testing, and deployment processes using CI/CD pipelines
• Analyze business requirements from financial stakeholders to deliver tailored data engineering solutions

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field
• 3+ years of professional experience in software engineering with a focus on big data technologies
• Proficiency in Python for developing scalable data processing applications
• Experience with cloud platforms such as AWS, Azure, or Google Cloud for large-scale data handling
• Strong understanding of data pipelines and ETL processes in a financial services context
• Ability to work with internal and third-party data sources while ensuring compliance with regulatory standards
• Demonstrated experience in agile development methodologies

Preferred Qualifications

• Master's degree in Computer Science or Data Science
• Experience in the financial services industry, particularly with banking data systems
• Familiarity with JP Morgan Chase's technology stack or similar enterprise environments
• Certifications in cloud computing (e.g., AWS Certified Big Data) or Python development
• Prior work on real-time data processing systems for fraud detection or risk management

Required Skills

• Python programming expertise for data-intensive applications
• Big data frameworks like Apache Spark, Hadoop, or Kafka
• Cloud computing platforms (AWS, Azure, GCP) for scalable processing
• SQL and NoSQL databases (e.g., PostgreSQL, MongoDB) for financial data management
• ETL tools and data pipeline orchestration (e.g., Apache Airflow)
• Version control systems like Git for collaborative development
• Agile and Scrum methodologies for team-based projects
• Data security and encryption techniques compliant with financial regulations
• Problem-solving and analytical thinking for complex data challenges
• Communication skills for stakeholder engagement in a global financial environment
• Experience with containerization (Docker) and orchestration (Kubernetes)
• Knowledge of machine learning basics for data preprocessing in finance
• Performance tuning and optimization of large-scale systems
• Familiarity with RESTful APIs for integrating third-party data sources

Benefits

• Competitive base salary and performance-based bonuses aligned with financial industry standards
• Comprehensive health, dental, and vision insurance coverage for employees and dependents
• Retirement savings plan with generous company matching contributions
• Paid time off including vacation, sick leave, and parental leave policies
• Professional development opportunities through JP Morgan's internal training programs and tuition reimbursement
• Employee stock purchase plan and other financial wellness benefits
• Flexible work arrangements, including hybrid options in Buenos Aires
• Access to global mobility programs and career advancement within JP Morgan Chase

JP Morgan Chase is an equal opportunity employer.