Data Engineer II

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 is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve.

Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations.

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 developing and delivering data solutions to accomplish technology and business goals and initiatives. Key responsibilities include performing code design and delivery tasks associated with the integration, cleaning, transformation, and control of data in operational and analytical data systems. Job expectations include working with stakeholders and Product and Software Engineering teams to aid with implementing data requirements, analyzing performance, and researching and troubleshooting data problems within system engineering domains.

•Partner with Product Owners, Data Scientists, Business Teams, and Technology to develop data products and AI-powered solutions.

•Drive the implementation of innovative data and analytics solutions.

•Translate complex requirements into scalable solutions; ask appropriate questions for clarification and take action accordingly.

•Design and develop end-to-end data pipelines leveraging ETL and modern development methodologies.

•Apply strong knowledge of Data Lake architecture, Python, Spark, SQL, object-oriented programming, and database concepts.

•Collaborate effectively with technical and non-technical stakeholders across functions.

•Manage multiple initiatives, timelines, and deliverables in a matrixed environment.

•Champion customer-centric insights and proactively take ownership of initiatives.

•Follow best practices in Data Governance and Quality standards.

Responsibilities:

• Works across development teams to contribute to the story refinement and delivery of data requirements through the delivery life cycle
• Leverages architecture components in solution development, codes solutions to integrate, clean, transform, and control data in operational and analytical data systems per acceptance criteria
• Builds processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management and defines and builds data pipelines and complex data sets to enable data-informed decision making, identifying and raising risks at all stages of the data engineering process
• Develops and executes test plans to produce quantitative results, contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies test issues and errors, and triages underlying causes
• Drives complex information technology projects to ensure on-time delivery and adheres to team delivery and release processes
• Identifies, defines, and documents data engineering requirements, communicating required information for deployment, maintenance, support, and business functionality
• Works with technology partners and a diverse set of stakeholders to identify and close gaps in data management standards adherence, negotiates paths forward, and helps identify and communicate solutions to complex data problems leveraging knowledge of information systems, techniques, and processes

Skills:

Required Skills:

• Python, Spark, SQL, object-oriented programming
• Tableau, Microstrategy, Power BI, Looker experience
•  End to End Data Pipeline Mgmt & Data Warehousing experience
• SQL & NoSQL Database Platforms &  Data Lake  concepts
• Data Product Delivery life cycle experience
• Great communication skills to effectively engage with technical and non-technical stakeholders across functions
• Abilities to effectively manage multiple projects and priorities

• 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

Desired Skills:

•  Containerization tools Docker/ Kubernetes
•  Data Pipeline Mgmt, MLOps
•  Data Mesh, Data Lake and SQL/NoSQL Databases experience

Shift:

Hours Per Week: