Manager - Data Engineering and Analytics

About the Company

Bank of America focuses on improving financial lives by leveraging every connection through responsible growth aimed at benefiting clients, employees, communities, and shareholders. We are dedicated to maintaining an inclusive and supportive work culture, fostering career growth, and encouraging innovation. The organization emphasizes an in-office culture that promotes collaboration, engagement, and career development with flexibility according to business needs.

About the Role

Our Global Business Services division offers technology and operational capabilities worldwide to support lines of business and staff functions, known for excellence in execution, risk management, and innovation. This position is focused on strengthening our Strategies, Analytics & Process Integration team based in India, dedicated to enhancing fraud detection and reducing losses.

Key Responsibilities

• Design, develop, and optimize scalable data pipelines using Python and PySpark within big data ecosystems such as Spark and Hadoop.
• Create and manage end-to-end data ingestion and transformation workflows that handle large, complex datasets for analytics and model preparation.
• Automate data workflows to eliminate manual tasks by implementing orchestration, monitoring, and recovery systems.
• Build reliable data infrastructures supporting downstream analytics, machine learning, and fraud detection solutions.
• Implement data quality checks, validations, and anomaly detection to ensure accurate and trustworthy datasets.
• Architect and maintain real-time and near-real-time data pipelines enabling fast operational insights.
• Collaborate with data scientists, product owners, and stakeholders to define data requirements and establish a unified, customer-level data view.
• Contribute to developing the data strategy for client protection to ensure the availability and quality of real-time data that enables intelligent fraud decision-making.

Qualifications and Experience

• Advanced degree preferred in Statistics, Mathematics, Applied Sciences, Engineering, or a related quantitative field.
• Preferred technical certifications include SQL, GSQL, Cypher, Hive, Python, and PySpark.
• 5 to 8 years of relevant analytics experience, with at least 2 years in engineering focusing on PySpark and big data frameworks.
• Proven expertise in Python, PySpark, and SQL, with knowledge of big data systems and graph databases considered advantageous.
• Experience in U.S. financial services and domains like fraud, compliance, and risk is beneficial.
• Strong background in developing analytical solutions that deliver measurable financial impact, alongside capable project management and communication skills.
• Familiarity with commercial and model generation software, and data tools such as HUE and Hive is desirable.

Work Schedule and Location

This role requires working hours from 11:30 AM to 8:30 PM or 12:30 PM to 9:30 PM. The work location is Mumbai, India, requiring onsite presence.