Senior Data Engineer — AI Platform & Lakehouse (Hybrid)

Bank of America; Charlotte (NC); Hybrid; USD 125,000 - 145,000; Full time

Benefits offered by this job

Discretionary incentive

Benefits package

Job summary

Bank of America is seeking a data engineering professional to build AI-ready data products, pipelines, and platform standards for GPS. The role blends hands-on engineering with strategic influence across data and AI domains.

The position spans data engineering, AI enablement, and platform architecture, collaborating with Product Owners, Data Scientists, and business partners in a hybrid work model.

Qualifications

• Bachelor's degree in Computer Science, MIS, Finance, Statistics, or a related field required.
• 5+ years of hands-on Data Engineering experience building production-grade data pipelines.
• Advanced SQL expertise with performance tuning on large datasets.
• Strong programming in Python and Spark; OO design principles.
• Experience with modern data orchestration (Airflow) to build ETL/ELT workflows.
• Knowledge of Data Lake concepts, dimensional modeling, and data virtualization.

Responsibilities

• Build end-to-end data pipelines and a data lake using Python, Spark, SQL, and ETL/ELT.
• Move AI and GenAI solutions into production with product owners and partners.
• Define platform standards for data and AI across the organization.
• Engineer production-grade, scalable data pipelines with robust ETL practices.
• Own the data-to-insight lifecycle and ensure insights reach users.
• Champion data governance and quality with stakeholders.
• Lead projects from idea to production in a fast-paced enterprise.
• Keep customer focus, delivering reliable data solutions for clients.

Skills

Data Engineering

SQL

Python

Spark

Airflow

Data Lake

Data Modeling

Communication

Problem Solving

Architecture

Education

Bachelor's degree in Computer Science, MIS, Finance, Statistics, or a related field

Tools

Airflow (Apache)

dbt

Spark

Databricks

Snowflake

Job description

Bank of America is seeking a data engineering professional to build AI-ready data products, pipelines, and platform standards for GPS. The role blends hands-on engineering with strategic influence across data and AI domains.

The position spans data engineering, AI enablement, and platform architecture, collaborating with Product Owners, Data Scientists, and business partners in a hybrid work model.