Engineering-Dallas-Associate, Product Management-10496460

Goldman Sachs • Dallas, TX

19h • Onsite

About The Position

Manage and execute projects and programs across multi-disciplinary Data Engineering initiatives within Product Operations (ProductOps), including defining project and program roadmaps, scoping deliverables, tracking milestones, identifying and escalating risks, and driving resolution of open action items. Assist in designing, implement, and maintain the Product Feature Request framework, OKRs, and milestone tracking processes to govern the product management lifecycle for Data Engineering, including its open-source code base, ensuring transparency and accountability across all product operations. Prepare and deliver progress reports, risk assessments, and program status updates to senior leadership and stakeholders across Data Engineering and firmwide client teams. Apply AI-driven analytics and automation techniques across product operations workflows, including leveraging AI within Jira for backlog analysis, trend identification, and operational reporting. Coordinate with engineering, risk, and business stakeholders to define, document, and communicate technical and functional requirements for Data Engineering platform features, ensuring alignment with enterprise risk remediation priorities. Operate within Agile software development lifecycle (SDLC) methodologies, utilizing cloud-based platforms, GitLab for version control and CI/CD workflows, and Markdown for technical documentation and knowledge management. Develop and maintain dashboards, issue management metrics, and data quality controls using Jira (including JQL) and supplementary tooling to monitor product health, team velocity, and delivery outcomes.

Requirements

• Master’s degree (U.S. or foreign equivalent) in Computer Science, Information Systems Management or a related field and one (1) year of experience in the job offered or a related role OR Bachelor’s degree (U.S. or foreign equivalent) in Computer Science, Information Systems Management or related field and three (3) years of experience in the job offered or a related role.
• Performing project management within product operations for a mixed, proprietary & open-source code base, including defining and enforcing best practices for product feature request intake frameworks, OKRs, and milestone-based delivery tracking.
• Working with cloud technologies, including AWS, Azure, or GCP, in the design, deployment, or operational support of enterprise data engineering platforms.
• Cross-functional stakeholder management and senior executive reporting on board-level programs, including preparing and delivering program status and risk summaries.
• Utilizing SQL and Python for data analysis, building data quality controls, and developing issue management metrics and dashboards using tooling such as Tableau or Power BI.
• Applying data analytics techniques to support project management.
• Leading risk remediation efforts within financial services firm, including scoping remediation programs, tracking resolution of findings, and reporting outcomes to senior management.

Responsibilities

• Manage and execute projects and programs across multi-disciplinary Data Engineering initiatives within Product Operations (ProductOps).
• Define project and program roadmaps, scope deliverables, track milestones, identify and escalate risks, and drive resolution of open action items.
• Assist in designing, implementing, and maintaining the Product Feature Request framework, OKRs, and milestone tracking processes for Data Engineering.
• Prepare and deliver progress reports, risk assessments, and program status updates to senior leadership and stakeholders.
• Apply AI-driven analytics and automation techniques across product operations workflows.
• Coordinate with engineering, risk, and business stakeholders to define, document, and communicate technical and functional requirements for Data Engineering platform features.
• Operate within Agile software development lifecycle (SDLC) methodologies.
• Develop and maintain dashboards, issue management metrics, and data quality controls using Jira and supplementary tooling.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level