Data Engineer I - Wholesale Credit Delivery

Truist•Atlanta, GA

2d•Onsite

About The Position

The Data Engineer 1 is responsible for sourcing, analyzing, documenting and maintaining data assets related to assigned portfolio and operational processes. Ensure processes deliver data that are accurate, complete, current, understandable and accessible. This entry level role will work towards gaining expertise and knowledge across multiple lines of business.

Requirements

Bachelor's degree and 5+ years of experience in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering.
Some experience with data engineering and ability to manage small data volumes.
Familiarity with data extraction in a variety of environments (e.g., SQL, SAS, etc.).
Experience in managing assigned projects with tight deadlines in a collaborative environment.
Grow to a high level of competency in statistical and analytical principles, tools, and techniques.
English (Required) language fluency.

Nice To Haves

Master's degree in field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering.
8+ years of experience in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science or Engineering
Demonstrate understanding of data analytics life cycle methodologies including data cleansing and preparation methodologies
5+ years of experience in data analytics, reporting, business intelligence, data engineering, portfolio analytics, or related roles.
Advanced experience with Python, SQL, business intelligence, and visualization tools.
Experience supporting credit, portfolio management, risk, banking, or financial services functions.
Experience developing executive dashboards, management reporting frameworks, and automated reporting environments.
Knowledge of data governance, regulatory reporting, and data quality controls.

Responsibilities

Support development and maintenance of data sources for projects, information needs and business requirements.
Build understanding of critical application systems and ability to transform data assets to aid in consumption by Business Information developers, decision & data scientists across the bank.
Learn the full array of data tools including static, SQL, R, Python, SAS to organize and format data assets by defining requirements and implementing automated repeatable solutions.
Deliver assigned ad hoc data pulls and analysis. Partner with more senior data engineers for guidance and mentoring.
Support solutions and recommendations for improving data integrity issues. Conduct research to determine the course of action to correct the data, identify, analyze and interpret trends and patterns in datasets.
Follow appropriate security, compliance, privacy considerations and follow data management guidance.
Foster communication and partnership across core team and junior-level managers.