Associate Software Engineer--Python & Data Analytics

Truist•Richmond, VA

1d•$90,000 - $120,000•Onsite

About The Position

Designs, develops, tests, and maintains Python-based software and data analytics solutions supporting Brokerage business processes, operations, and decision-making. Translates brokerage data and user needs into scalable, reliable, and well-controlled applications, data pipelines, analyses, and reporting capabilities. Collaborates with Brokerage product, operations, risk, data, and technology partners to deliver solutions that meet business requirements, data-quality standards, and applicable financial-services controls. For this opportunity, Truist requires unrestricted, permanent U.S. work authorization. Truist will not sponsor an applicant for work visa status or employment authorization, nor will we offer any immigration-related support for this position (including, but not limited to H-1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN-1 or TN-2, E-3, O-1, or future sponsorship for U.S. lawful permanent residence status.)

Requirements

Bachelor’s degree and 3 years of experience or equivalent education and software engineering training or work-related experience.
In-depth knowledge of information systems with the ability to identify, apply, and implement IT best practices.
Understanding of key business processes and competitive strategies related to the IT function.

Nice To Haves

Bachelor’s degree and 3 years of experience or equivalent education and software engineering training or work-related experience
Experience supporting Brokerage, broker-dealer, wealth management, capital markets, or finncial-services operations.
Knowledge of brokerage concepts and data, such as client and account records, securities, positions, balances, trades, transactions, products, fees, suitability, supervision, or regulatory reporting.
Experience using common Python data and analytics libraries, such as pandas, NumPy, PySpark, or equivalent frameworks.
Experience developing dashboards, operational reporting, or data visualisations using tools such as Power BI or Tableau.
Experience with low-code or no-code solutions, including Microsoft Power Platform (Power Apps, Power Automate, and Power BI), SharePoint, or Salesforce.
Experience integrating low-code solutions with APIs, databases, enterprise data platforms, or workflow processes while applying appropriate governance and support standards.
Experience with cloud data platforms, distributed processing, or enterprise analytics environments.
Experience with Git-based source control, continuous integration and delivery practices, automated testing, and open-source tools or frameworks.
Familiarity with financial-services controls, data governance, privacy, risk management, and regulatory requirements applicable to Brokerage technology.

Responsibilities

Designs, develops, tests, and maintains Python applications, data pipelines, analytics routines, and reporting solutions that support Brokerage products, operations, and control processes.
Acquires, cleanses, transforms, reconciles, and analyses brokerage data from internal and external sources, including account, client, transaction, position, product, and operational datasets.
Produces reusable analyses, dashboards, and data products that help Brokerage partners monitor business performance, service levels, exceptions, risk indicators, and operational trends.
Works with Brokerage product owners, operations, data stewards, risk partners, and technology teams to translate business requirements into well-defined technical and analytical solutions.
Applies software engineering practices to Python code, including modular design, source control, peer review, automated testing, documentation, and secure development standards.
Implements data-quality checks, lineage, reconciliation, exception handling, and audit-ready controls appropriate for a regulated broker-dealer environment.
Troubleshoots data defects, production incidents, performance issues, and analytical discrepancies; performs root-cause analysis and implements sustainable corrective actions.
Participates in the full delivery lifecycle, including requirements refinement, solution design, development, testing, deployment, production support, and continuous improvement.
Integrates Python and analytics solutions with approved enterprise platforms, APIs, databases, file-transfer mechanisms, and workflow tools.
Communicates findings, risks, dependencies, and solution recommendations clearly to both technical and non-technical stakeholders.