Analytics Data Engineer III

Truist Bank•Atlanta, GA

9d•Onsite

About The Position

The incumbent will act as a data engineer responsible for sourcing, analyzing, documenting and maintaining data assets related to Truist's Retail Community Bank portfolio and operational processes. Ensure processes deliver data that are accurate, complete, current, understandable and accessible. The incumbent will be aligned to multiple lines of business (LOB) and will work towards gaining expertise on other LOBs as well. Responsible for leading projects end to end independently. Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.

Requirements

Bachelor's degree and 6+ years of experience in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering.
Demonstrated knowledge and skill in data warehousing and transactional application data concepts and technology.
Proven experience with data engineering and ability to manage large data volumes.
Candidate should demonstrate understanding of data analytics life cycle methodologies including data cleansing and preparation methodologies, including regex, filtering, indexing, interpolation, and outlier treatment.
Strong familiarity with data extraction in a variety of environments (e.g., SQL, JQuery, etc.).
Experience in managing multiple projects with tight deadlines in a collaborative environment.
Maintain a high level of competency in statistical and analytical principles, tools, and techniques.
Incumbent should have an understanding of various 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 demonstrated proficiency in Microsoft Office Suite (Excel, PowerPoint, Word)

Nice To Haves

Master's degree in field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering.
10+ years of experience in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science or Engineering

Responsibilities

Lead research, analyze, design, develop and/or maintain data sources in support of projects, information needs and business requirements. Perform analysis, validation and interpretation of outputs. Take ownership of issues through resolution, including close coordination between LOB partners and data engineers.
Have a deep understanding of various quantitative analysis principles and ability to transform data assets to aid in consumption by decision & data scientists across the bank.
Utilize the full array of reporting technique options including static, OLAP, and dashboard functionality dependent on specifications and abilities. Work closely with senior management and BI Architecture and Reporting Managers concerning data organization, transformations, formatting, OLAP, tool choices etc. to define and implement reporting objectives.
Partner with LOB analytics groups through frequent communication and the creation of periodic user forums. Participate in internal and external forums to share knowledge and keep abreast with latest technological advancement around the banking industry.
Develop training material and user documentation as it relates to data and report retrieval. Instruct, direct and mentor team members and LOB partners on new products and reporting tools. Train and guide team members in coding efficiently and accurately.
Prioritize and manage ad hoc reporting efforts by providing clear expectations to LOB partners and management.
Develop solutions and recommendations for improving data integrity issues. Analyze data issues and work with development teams for problem resolutions. Identify problematic areas and conduct research to determine the best course of action to correct the data, identify, analyze and interpret trends and patterns in complex datasets.
Foster communication and partnership across multiple levels of the organization including engagement with mid-level managers.