Sr Data Engineer

Job Description:

At Bank of America we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients teammates communities and shareholders every day.

Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed build a career and contribute to our shared success. This includes attracting and developing exceptional talent recognizing and rewarding performance and supporting our teammates physical emotional and financial wellness through affordable competitive and flexible benefits.

We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service community college education or a wide range of work and life experiences. These journeys foster resilience leadership and innovation strengthening our workforce and positively impact the communities we serve.

Bank of America is committed to an in-office culture that supports collaboration engagement and career development. Our approach includes clear in-office expectations while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.

At Bank of America you can build a successful career with opportunities to learn grow and make an impact. Join us!

Job Description:

What were building

Our team runs a range of data and AI projects across the GPS business.

A few examples:

A modern AI-ready data platform and lakehouse that supports analytics machine learning and generative AI across the org.

AI-powered tools that give sales and product teams fast reliable answers to product servicing and client questions.

Models that optimize pricing and foreign-currency conversion to drive real business value.

Real-time pipelines that turn raw client and servicing data into insights teams can act on.

Who were looking for

This is a hybrid role that spans data engineering AI product enablement and platform architecture. Youll build and scale the data backbone behind AI at GPS: engineering AI-ready data products helping shape platform direction and taking solutions from idea to production. We want someone who enjoys both the hands-on craft of building strong data platforms and the bigger opportunity to influence how the organization delivers AI. Whether you lean engineer or lean strategist theres room here to do both.

Responsibilities

Build the data foundation for AI. Design and deliver end-to-end pipelines and Data Lake architecture using Python Spark SQL and modern ETL practices turning large raw datasets into trusted AI-ready data products.

Enable AI products through data. Work with Product Owners Data Scientists and business partners to move AI and GenAI solutions into production turning business problems into reusable data capabilities.

Set platform standards. Define the architecture patterns and standards for how data and AI get built deployed and used across the org with an eye on reusability performance and cost.

Engineer production-grade solutions. Apply Object-Oriented design solid data platform concepts and strong ETL practices to build reliable scalable pipelines and help shape where the teams data capabilities go next.

Own the data-to-insight lifecycle. Review and improve data-flow processes understand how data gets consumed and make sure insights reach the people who use them.

Champion trusted governed data. Build Data Governance and Quality principles into your work and act as a reliable partner to stakeholders and data consumers.

Drive projects from idea to production. Take new concepts and deliver them across business and Enterprise IT partnerships in a fast-paced environment.

Keep the customer first. Anticipate needs take initiative and deliver solutions that work well for internal and external customers.

Required Skills:

Bachelors degree in Computer Science Management Information Systems Finance Statistics or a related field required.

5 years of hands-on Data Engineering experience building and operating production-grade data pipelines and platforms.

Advanced SQL expertise deep proficiency in writing optimizing and tuning complex SQL and stored procedures across large-scale relational and distributed datasets (query performance window functions partitioning and data modeling).

Strong programming background in Python and Spark with solid Object-Oriented design principles and a focus on reusable testable production-quality code.

Modern data pipeline orchestration hands-on experience with Apache Airflow (or comparable modern schedulers) to build schedule and monitor reliable end-to-end ETL/ELT workflows.

Data Lake and modern platform architecture strong understanding of Data Lake concepts dimensional modeling data virtualization and modern data delivery methodologies (medallion/lakehouse patterns distributed processing).

Experience delivering Data & AI solutions within large matrixed organizations with the ability to quickly assess and adopt the right sourcing and architecture strategy.

Strong quantitative analytical and problem-solving skills paired with critical thinking and creativity.

Ability to build effective relationships with business and technology partners.

Outstanding verbal and written communication skills with the ability to express complex technical concepts in business terms across all levels of management.

Nice to have:

Modern data engineering & orchestration tooling such as Airflow dbt Spark and CI/CD for data pipelines (Git-based workflows automated testing and deployment).

Cloud and lakehouse platforms experience with modern cloud data warehouses and lakehouse technologies (e.g. Snowflake Databricks Delta Lake) alongside distributed storage (HDFS Hive Apache Spark).

Advanced SQL & database platforms performance tuning and engineering across RDBMS and Big Data platforms such as Oracle Exadata SQL Server and Teradata.

ETL/ELT and streaming technologies Python Spark SSIS shell scripting and exposure to real-time/streaming frameworks (e.g. Kafka).

BI and data visualization Tableau (Desktop and Server) Power BI SSRS and SSAS.

AI/GenAI enablement familiarity with building data foundations that support machine learning and generative AI use cases.

Banking and Global Treasury transactions industry experience a plus.

Skills:

• Analytical Thinking

• Application Development

• Data Management

• DevOps Practices

• Solution Design

• Agile Practices

• Collaboration

• Decision Making

• Risk Management

• Test Engineering

• Architecture

• Business Acumen

• Data Quality Management

• Financial Management

• Solution Delivery Process

Shift:

1st shift (United States of America)

Hours Per Week:

40

Pay Transparency details

US - NY - New York - ONE BRYANT PARK - BANK OF AMERICA TOWER (NY1100)

Pay and benefits information

Pay range

$125000.00 - $145000.00 annualized salary offers to be determined based on experience education and skill set.

Discretionary incentive eligible

This role is eligible to participate in the annual discretionary plan. Employees are eligible for an annual discretionary award based on their overall individual performance results and behaviors the performance and contributions of their line of business and/or group; and the overall success of the Company.

Benefits

This role is currently benefits eligible. We provide industry-leading benefits access to paid time off resources and support to our employees so they can make a genuine impact and contribute to the sustainable growth of our business and the communities we serve.