Data Analytics
$146,806–$176,000 year
HybridBoston, Massachusetts, United States
Job Summary
Collaborate with internal technical teams, SaaS Ops, and clients to resolve data issues and support defect resolution by identifying root causes and debugging production anomalies. Act as a data subject matter expert to understand data relationships, fix time-critical SQL DML issues, and contribute to new data service integrations through requirements gathering and testing. Document product specifications, prepare business cases for development, and enforce standard operating procedures covering triage, escalation, and stakeholder communication. Continuously assess and implement enhancements to improve issue monitoring and data governance across front, middle, and back office support functions.
Required Qualifications
- Bachelor's degree or its equivalent in Computer Science, Information Systems, or a related field
- 5 years of related experience in Finance and Banking industries
- Master's degree or its equivalent in Computer Science, Information Systems, or a related field
- 3 years of related experience in Finance and Banking industries
- Demonstrated solid communication skills across all channels and levels of recipients including team members, colleagues, and clients at all levels
- Demonstrated strong problem solving skills
- Deep understanding of the financial data to understand what the problem is when an issue occurs
- Proven experience managing data as front, middle, and back office support
- Proven experience with financial services data domains – security master, benchmarks positions, transactions, cash, performance, and/or analytics
- Demonstrated strong proficiency in SQL
- Demonstrated knowledge of data management, data governance, service catalogue, data lineage tools, operational dash boards, and process monitoring tools
- Working knowledge of at least one of the following: Azure cloud platforms, Kettle, Talend, Qlik Replicate, Qlik Compose, Kafka, or Snowflake
- Demonstrated knowledge of internal and external integrations, triage issues, and ability to implement/recommend solutions to data problems and anomalies
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