Sr Lead Software Engineer- Data

Location: New York, NY, United States

Job Family: Software Engineering

About the Role

At JP Morgan Chase, we are at the forefront of financial innovation, and our technology teams are pivotal in driving that transformation. As a Sr Lead Software Engineer - Data, you will join an agile team dedicated to enhancing, building, and delivering cutting-edge technology products that power our global financial services. Based in the heart of New York, NY, you will contribute to solutions that handle vast amounts of sensitive data from trading platforms, client portfolios, and risk analytics, ensuring our firm remains a leader in investment banking, consumer finance, and asset management. Your role will involve architecting robust data systems that support real-time decision-making in a highly regulated environment, where precision and security are paramount. In this senior leadership position, you will guide the development of scalable data pipelines and analytics platforms using technologies like Spark, Kafka, and cloud services on AWS. You will collaborate with cross-functional teams, including data scientists, product managers, and compliance experts, to integrate AI-driven insights into our core offerings, such as fraud detection and market forecasting. Emphasizing agile practices, you will lead sprints to deliver high-impact features while adhering to strict data governance standards, including those set by the SEC and global privacy laws. Your expertise will help optimize our infrastructure to process petabytes of financial data efficiently, reducing latency and costs in our dynamic market operations. We value innovation and continuous learning at JP Morgan Chase, providing opportunities to explore emerging trends like blockchain for secure data sharing and machine learning for predictive modeling. As a key player in our technology ecosystem, you will mentor emerging talent, foster a culture of excellence, and contribute to products that serve millions of clients worldwide. This role offers not just technical challenges but a chance to shape the future of finance through data excellence, all while enjoying the vibrant energy of New York and the support of a world-class organization committed to your professional growth.

Key Responsibilities

• Lead the design, development, and deployment of advanced data engineering solutions to support JP Morgan Chase's financial products and risk management systems
• Collaborate with agile teams to build scalable data pipelines that process terabytes of market, transaction, and client data in real-time
• Mentor junior engineers and drive best practices in data architecture, ensuring high availability and fault tolerance in mission-critical applications
• Integrate machine learning models into data workflows to enhance predictive analytics for trading, fraud detection, and portfolio optimization
• Ensure compliance with regulatory requirements by implementing robust data security measures and audit trails
• Optimize data storage and retrieval systems using cloud-native services to reduce costs and improve efficiency in JP Morgan's global operations
• Conduct code reviews, performance tuning, and troubleshooting to maintain system reliability during peak financial market activities
• Partner with stakeholders across investment banking, consumer banking, and asset management to align data solutions with business objectives
• Innovate by exploring emerging technologies like AI and big data tools to push the boundaries of JP Morgan's technology products

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field; advanced degree preferred
• 8+ years of experience in software engineering, with a focus on data engineering and big data technologies
• Proven track record in developing scalable data pipelines and solutions in a financial services environment
• Strong understanding of data governance, security, and compliance standards such as GDPR and SEC regulations
• Experience leading cross-functional teams in agile methodologies within high-stakes financial projects
• Proficiency in cloud platforms like AWS, Azure, or Google Cloud, with emphasis on data storage and processing
• Demonstrated ability to handle large-scale data sets and optimize performance in production environments

Preferred Qualifications

• Master's degree in Data Science or related field
• Experience with machine learning frameworks and AI-driven data analytics in finance
• Prior work at a major financial institution, such as investment banking or asset management
• Certifications in relevant technologies like AWS Certified Data Analytics or Google Professional Data Engineer
• Knowledge of blockchain or distributed ledger technologies for financial data applications

Required Skills

• Java or Python programming expertise
• Big data technologies like Hadoop, Spark, and Kafka
• SQL and NoSQL databases (e.g., PostgreSQL, MongoDB)
• Cloud computing platforms (AWS, Azure)
• Data modeling and ETL processes
• Machine learning libraries (TensorFlow, PyTorch)
• Agile methodologies and DevOps tools (Jenkins, Docker)
• Financial domain knowledge (e.g., risk modeling, trading systems)
• Problem-solving and analytical thinking
• Leadership and team collaboration
• Attention to detail in data accuracy and security
• Communication skills for stakeholder engagement
• Version control systems (Git)
• Performance optimization techniques
• Regulatory compliance awareness in finance

Benefits

• Competitive base salary and performance-based annual bonuses
• Comprehensive health, dental, and vision insurance coverage
• 401(k) retirement savings plan with generous company matching
• Paid time off, including vacation, sick days, and parental leave
• Professional development programs and tuition reimbursement for advanced certifications
• Employee stock purchase plan and financial wellness resources
• On-site fitness centers, wellness programs, and mental health support
• Flexible work arrangements, including hybrid options in New York

JP Morgan Chase is an equal opportunity employer.