Senior 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:

This job is responsible for driving data engineering efforts to deliver enterprise-wide capabilities and complex data solutions. Key responsibilities include directing code design and delivery tasks associated with the integration, cleaning, transformation, and control of data in operational and analytical data systems and working with the Project Management team to define outcomes and inform work structures. Job expectations include providing technical thought leadership by implementing complex data solutions and interactions across multiple systems and domains.

Overview:

Lead requirement analysis, high-level and low-level design, development, and implementation of enterprise-scale data platforms and integration solutions leveraging Spark/Scala, Kafka, Hadoop, Starburst, Cloud technologies, Object Storage, and Informatica.

Lead developer experience with ability to conduct design reviews, mentor / coach development teams, and produce comprehensive yet flexible solution designs.

Ensures that the design and engineering approach for complex features are consistent with the larger portfolio solution

Key experience developing and delivering complex software requirements to accomplish business goals

Capability to ensure software is developed to meet functional, non-functional, and compliance requirements

Successful background ensuring solutions can be integrated successfully into the overall application/system with clear, robust and well-tested interfaces

Should be able to lead multiple projects concurrently each with competing deadlines.

Should be knowledgeable in Treasury Payments and Deposits domains.

Serves as a fully seasoned/proficient technical resource; provides technical knowledge and capabilities as team member and individual contributor.

Typically 10 or more years of data delivery/integration experience

Works under minimal supervision

Has the knowledge of Hadoop Spark/Spark Streaming best practices and standards as well as standard software development lifecycle experience.

Must have an understanding of our ability to quickly grasp technology concepts

Solid quantitative, analytical, process development, facilitation skills, and organizational skills required

Strong communication, presentation, interpersonal, software development and work management skills are essential

Coordinate with deployment and support teams and ensure projects are successfully deployed into testing and Production environments.

Development experience using Agile process

Experience in designing, developing and deploying Real time and Near real time & batch data integration solutions

Work with people in different time zones & teams

Responsibilities:

Assembles large, complex data sets that meet functional and non-functional requirements, ensuring that the design and engineering approach is consistent across multiple systems

Maintains, improves, cleans, and manipulates large data for operational and analytics data systems, builds complex processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management, and communicates required information for deployment, maintenance, and support of business functionality

Utilizes multiple architectural components in the design and development of client requirements and collaborates with development teams to understand data requirements and ensure the data architecture is feasible to implement

Defines and builds data pipelines to enable data-informed decision making, ensuring adherence to release processes and risk management routines

Contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies any test issues and errors, and leads triage of underlying causes

Leads the identification of gaps in data management standards adherence and works with appropriate partners to develop plans to close gaps, leading concept testing and conducting research to prototype toolsets and improve existing processes

Mentors Data Engineers in the delivery and release of continuous integration and continuous delivery events and defines key performance indicators and internal controls

Required Qualifications:

10+ years of experience with Data Engineering

Experience with large-scale analytical platforms, metadata-driven architectures, and distributed data processing frameworks is preferred.

Design and implement cloud-native data platforms utilizing Object Storage, Data Lakehouse architecture, distributed query engines, and streaming technologies to support real-time, near real-time, and batch processing requirements.

Hands on experience in Scala, Spark, Kafka Streaming

Very good understanding of Hadoop components, architecture & tool sets: Spark and Scala, Informatica, Starburst, Object Storage in enterprise data platforms

Must have Architected, developed & implemented solutions using real time streaming technologies

Good knowledge of performance tuning

Experience working with Exadata & Oracle SQL Tuning

Experience working with Starburst and Object Storage

Experience developing Streaming/Near Real time and Batch data integration solutions.

Hands on experience in UNIX Shell Scripting

Working experience with scheduling tools

Desired Qualifications:

CICD Build & Deployment tools

API development experience

Financial Services / Banking experience

Experience in distributed computing

Experience with open table formats such as Apache Iceberg, Delta Lake, or equivalent technologies

Experience with enterprise metadata management, data lineage, governance, and data quality frameworks

Skills:

Analytical Thinking

Application Development

Data Management

Risk Management

Solution Design

Agile Practices

Architecture

Collaboration

Decision Making

DevOps Practices

Business Acumen

Data Quality Management

Financial Management

Solution Delivery Process

Test Engineering

Shift: 1st shift (United States of America)

Hours Per Week: 40