Analytics Data Engineer III

The Analytics Data Engineer III role at Truist Bank is based onsite in Atlanta, GA. This position centers on sourcing, analyzing, documenting, and maintaining data assets for the Retail Community Bank portfolio and its operational processes, coordinating with multiple lines of business and leading end-to-end data initiatives.

Responsibilities

• Own the end-to-end sourcing and maintenance of data sources that support projects and business requirements, including research, design, development, and ongoing upkeep. Perform analysis, validation, and interpretation of outputs, driving issue resolution in close collaboration with LOB partners and data engineers.
• Apply a strong understanding of quantitative analysis principles to transform data assets for use by decision makers and data scientists across the bank.
• Choose and implement reporting approaches ranging from static outputs to OLAP and dashboards, based on specifications. Collaborate with senior management and BI architecture and reporting teams on data organization, transformations, formatting, OLAP considerations, and tool selections to achieve reporting objectives.
• Coordinate with LOB analytics groups through regular communication and periodic user forums. Engage in internal and external forums to share knowledge and stay current with advances in banking technology.
• Create training materials and user documentation related to data access and report retrieval. Mentor team members and LOB partners on new products and reporting tools, and coach colleagues in efficient and accurate coding.
• Prioritize ad hoc reporting requests by setting clear expectations with LOB partners and management.
• Develop solutions and recommendations to improve data integrity; analyze data issues and collaborate with development teams to resolve them. Identify problematic areas, research corrective actions, and analyze trends and patterns in complex datasets.
• Promote cross-organizational collaboration across multiple levels of management, including engagement with mid-level managers.

Requirements

• A bachelor’s degree and at least six years of experience in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering.
• Proven knowledge of data warehousing and transactional data concepts and related technologies.
• Experience in data engineering with the ability to manage large data volumes.
• Understanding of data analytics life cycle methodologies, including data cleansing and preparation techniques such as regex, filtering, indexing, interpolation, and outlier treatment.
• Strong familiarity with data extraction across diverse environments (SQL, JQuery, etc.).
• Experience managing multiple projects with tight deadlines in a collaborative environment.
• Proficiency in statistical and analytical principles, tools, and techniques.
• Knowledge of multiple database environments (IBM DB2, Oracle, Netezza), technical programming skills (SAS, SQL, Toad), exposure to applied data science tools (R, Python, SAS E-Miner), familiarity with data visualization and BI tools (Tableau, MicroStrategy), and proficiency in Microsoft Office Suite (Excel, PowerPoint, Word).

Technologies

• SQL
• JQuery
• IBM DB2
• Oracle
• Netezza
• SAS
• Toad
• R
• Python
• SAS E-Miner
• Tableau
• MicroStrategy
• Excel
• PowerPoint
• Word

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• Life insurance
• Disability insurance
• Accidental death and dismemberment
• Tax-preferred savings accounts
• 401k plan
• Vacation days
• Sick days
• Paid holidays
• Defined benefit pension plan
• Restricted stock units
• Deferred compensation plan