Tradeweb
Website:
tradeweb.com
Job details:
Designation: Senior Data Researcher – Customer Data Management
Shift Time: UK (12 PM IST - 9 PM IST)
Work Mode: 3 Days WFO
Skills: Customer Data, Data Management, Data Researcher, SQL, Zoom Info, Fact-set and D&B
Note: Looking for Immediate to 30 days' Notice Period Max.
Group Details
As a Senior Data Researcher within the Customer Data Management team at Tradeweb, you will play a key role in ensuring the accuracy, consistency, and scalability of core customer data across the organization. This includes high-value datasets such as Business Entity, Business Industry Classification and Contact Data.
You will be responsible for mastering entity data, supporting data alignment initiatives, and driving improvements in data quality and operational efficiency. This role goes beyond traditional data research, requiring a proactive approach to identifying opportunities for automation, improving processes, and enhancing how data is managed and consumed across the business.
Reporting to the Customer Data Lead, you will operate both independently and in close partnership with cross-functional teams including Sales, Finance, Compliance, Risk, and Data Platform. Leveraging strong analytical capability, clear communication, and a solutions-focused approach, you will help deliver scalable, high-quality data management practices that support business, regulatory, and risk management objectives across Tradeweb.
Job Responsibilities
- Master and maintain entity data within the firm’s centralized data systems, ensuring accuracy, consistency, and proper hierarchy alignment across datasets.
- Manage the onboarding of new acquisitions and datasets into the corporate data ecosystem, ensuring timely and accurate integration.
- Analyze and interpret client and entity data from multiple sources, reconciling discrepancies and determining appropriate data structures and hierarchies.
- Identify opportunities for data quality improvement and operational efficiency, including leveraging automation, AI tools, and scalable data processes to enhance efficiency and reduce manual effort.
- Implement and maintain data changes (creation, modification, activation/deactivation) in line with established governance and controls.
- Write and execute SQL queries to extract, validate, and analyze data as part of ongoing data management and improvement initiatives.
- Work with large and complex datasets, performing data manipulation, transformation, and reconciliation activities.
- Utilize Excel (including pivot tables, VLOOKUP/XLOOKUP) and other tools to support data analysis and reporting.
- Collaborate closely with cross-functional stakeholders to gather requirements, resolve data issues, and ensure alignment on data definitions and usage.
- Clearly document data processes, business rules, and project requirements to support transparency and scalability.
- Contribute to data-related projects and initiatives, including data alignment, cleansing, and platform improvements.
Qualifications & Experience
- Bachelor’s degree or equivalent experience; postgraduate qualification (e.g., MBA Finance) is advantageous.
- 3-5+ years of experience in data research, data management, or a related field, preferably within financial services.
- Strong understanding of financial markets data and entity structures (e.g., corporate hierarchies, parent/ultimate parent relationships).
- Demonstrated experience working with large datasets and performing data analysis, reconciliation, and validation.
- Working knowledge of SQL, with the ability to write and execute basic queries.
- Intermediate to advanced Excel skills, including pivot tables, VLOOKUP/XLOOKUP, and data manipulation techniques.
- Experience with Python (e.g., pandas for data analysis and automation) is advantageous.
- Strong analytical and problem-solving skills, with the ability to synthesize information from multiple sources.
- Excellent stakeholder management and communication skills, with the ability to work effectively across teams.
- Highly organized, detail-oriented, and able to manage multiple priorities in a fast-paced environment.
- Self-motivated with a proactive approach to identifying improvements and driving outcomes.
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