About the position
As a Data Management Product Owner/Analyst with the Controls Management Data Governance team, you will be responsible for ensuring data is fit for reporting which includes ingesting data to reporting platform, ensuring all controls related to data quality are in place. You will establish data reconciliation, metadata registration, data validation and help support outbound data feeds and feed governance. The Controls Management mission is to solidify an effective Firmwide control framework within and across the lines of business by identifying and remediating control issues with a sense of urgency, regardless of the source. The Controls Management team will work collaboratively with other control disciplines and will oversee existing control functions as well as the development of new control functions and protocols. This process will enable the firm to engage the appropriate teams in a timely manner and provide the ability to quickly remediate critical control issues across all the impacted areas of the firm. The Controls Management Controls Room is a Firmwide Reporting Utility that provides standardized control-related data and drives quicker, efficient and accurate reporting. It's an information warehouse with capabilities for reporting, visualizations and analytics. Its primary goal is to enhance control oversight and efficiency through the standardization and automation of operational risk reporting, provide access to Firmwide aggregated information and produce business risk insight.
Responsibilities
- Demonstrate good understanding of data governance framework, data quality & data lineage
- Implement and support Data Quality (DQ) practices. Define and manage data validation rules/reconciliations for critical data elements and other core attributes by running complex SQL queries
- Govern and triage DQ Issues as it progresses through the lifecycle
- Discover and document data-lineage to trace the end-to-end data journey from point of creation to consumption
- Set up data profiling and DQ rules leveraging DQ tools like RDHP (Reference Data Hosting Platform), Collibra, Informatica and other emerging tools
- Leverage productivity tools such as Alteryx and visualization tools such as Tableau to analyze large dataset to draw inferences
- Collaborate & Build strong partnerships with Business stakeholders & Technology teams to support data quality efforts
- Define data quality rules for critical data elements based on the Firmwide dimensions and obtain approval from Data Owner
- Demonstrates Teamwork by collaborating with others to integrate ideas & achieve common goals
- Set up ingestion of data sources to AWS public cloud and ensure data matches between source and target and support and feeds (API/KAFKA/Data Mesh) requirements
- Review data models to understand data concepts and relationships. Perform ad hoc analysis and data extracts using Databricks or Hue/Impala
- Onboard new data categories on reconciliation framework to ensure consistency is maintained between source and target systems
- Perform analysis, create visualization, presentations, wireframes and recertification steps on various data management components on ad hoc, quarterly and yearly basis
Requirements
- Quantitative background (BA/BS in Math, Statistics, Economics, Computer Science, Engineering) with 3-4+ years of experience working with technology partners to develop products
- Experience using Data Quality tools such as Informatica Data Quality (BDQ/IDQ), DQCS (Data Quality Control Services), AWS Glue or similar tools is experience required
- Experience implementing and supporting Data Quality (DQ) practices by running data profiling and interpreting profiling results for CDEs
- Experience defining and managing data validation rules/reconciliations for critical data elements and other core attributes by running complex SQL queries
- Experience using analytics and visualization tools/libraries (Tableau, Alteryx, etc.) to distill findings into insightful analytical solutions for stakeholders
- Experience translating user requests to technology requirements using agile management tools like JIRA
- Experience working with large complex data sets, understanding algorithm, drawing conclusions, and reporting DQ findings
- Excellent written and verbal communications skills. Must be able to communicate with a wide variety of functional groups at various levels
- Effective time management and multitasking skills
- Strong SQL, DataBricks, Excel and PowerPoint is a must have
- Flexible, adaptable to shifting priorities; able to work in a fast-paced, results driven environment
- Experience using metadata management tools such as Informatica/Collibra, RDHP and Jade Catalog
Nice-to-haves
- An understanding of the agile methodology
- Experience project managing small to large scale projects
- Experience working with internal control and risk management is a plus
- Strong background and understanding of big data and AWS Public Cloud environment and tools
- Enthusiastic, self-motivated, effective under pressure and willing to take personal responsibility/accountability
- Financial services industry background with specific experience in data analysis, DQ reporting or risk and controls
