Controllers-Jersey City-Associate, Data Governance & Stewardship-10419015

Goldman Sachs•Jersey City, NJ

2d•Onsite

About The Position

The Associate, Data Governance & Stewardship role at Goldman Sachs & Co. LLC in Jersey City, New Jersey, focuses on building metrics and dashboards to provide business stakeholders and senior management with insights into data. This includes creating management information (MI), curating data adjustments, aggregating by division, and considering factors that influence customer decision-making and regulatory obligations. The role is central to influencing the strategic direction of data initiatives, authoring project documentation (data standards, reporting data dictionaries, data models), and collaborating with firmwide teams to shape data governance tooling. Responsibilities also include working with engineering teams to build data models and quality controls, reviewing and developing expertise in data lineage tools like 'Legend' (Alloy), and coordinating workstreams to document and digitize data lineage processes. Frequent project updates to stakeholders, sponsors, and users are also a key part of the role.

Requirements

Master’s degree (U.S. or foreign equivalent) in Business Analytics, Information Systems, Computer Engineering, or a related field and one (1) year of experience in data governance or analysis.
OR Bachelor’s degree (U.S. or foreign equivalent) in Business Analytics, Information Systems, Computer Engineering, or a related field and three (3) years of experience in data governance or analysis.
Utilizing MS Office Suite of applications to analyze large dataset, including pivot tables, VLOOKUP, index matching, and development of presentations.
Utilizing SQL and Python to extract, transform, model, and analyze structured data for reporting and analytics.
Working on dashboard and metrics development using business intelligence and analytics tools to drive data quality, and track issue management metrics.
Understanding data modeling concepts and technologies, such as SQL, JSON, or Python, to support development of firmwide enterprise models.
Utilizing problem solving and Lean Six Sigma techniques to perform root cause analysis, prioritize issues, and improve processes while collaborating with senior technologists and project managers.
Experience with product reference data, booking, settlement, or reconciliation functions in banking or financial services.

Responsibilities

Build metrics and dashboards to gain insight into data for business stakeholders and senior management.
Create management information (“MI”), curate data adjustments, and aggregate by division.
Consider parameters that impact customer decision making and regulatory obligations and reporting.
Influence the strategic direction for data initiatives.
Author project-related documentation, including data standards, reporting data dictionaries, and data models.
Work closely with firmwide teams to influence the tooling being developed to enable the data governance framework.
Collaborate with engineering teams to understand and build data models and data quality controls.
Review and develop expertise in traversing data models via enterprise tooling such as ‘Legend’ (internally known as Alloy) to ensure data governance tooling is working as intended.
Coordinate workstreams to document data lineage from source to target and work with engineering partners to digitize these processes.
Provide frequent project updates to project stakeholders, sponsors, and users of all levels.