Data Analytics Engineer
4703 Madison Yards Way, Suite 700, Madison, Wisconsin, 53705, United States, United States
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The State of Wisconsin Investment Board (SWIB)
View all jobs at The State of Wisconsin Investment Board (SWIB)
Job Description:
About the Team
The Data Delivery and Operations division is a growing, client-focused team dedicated to enabling data-driven decision-making across the organization. We are business-centric and work in close partnership with Investment Management, Operations, and Technology to anticipate and meet SWIB’s complex data and reporting needs. In collaboration with Technology, we are transforming SWIB into a premier data-driven investment organization.
Position Overview
Reporting to the Data Analytics Engineering Manager, the Data Analytics Engineering Analyst plays a critical role in managing and advancing SWIB’s data management practices—specifically for Security Master and Entity Master data. This role drives the implementation of data quality frameworks, data governance principles, and data stewardship practices across the investment data landscape.
The Analyst collaborates cross-functionally with business owners, technology teams, and external providers to ensure that investment master data is accurate, timely, and aligned with enterprise data standards. This position also helps shape the design and implementation of key data management tools and technologies, with an emphasis on data quality monitoring, issue resolution workflows, and integration with downstream systems such as FactSet, MSCI, Aladdin, Bloomberg PORT, and Charles River (CRD).
Essential activities:
- Serve as a Subject Matter Expert (SME) for Security and Entity Master Data at SWIB.
- Govern and maintain high-quality investment master data to support real-time, daily, monthly, and quarterly reporting needs.
- Partner with stakeholders in Investment Management, Operations, and Technology to gather requirements and align data strategies with business needs.
- Collaborate on the implementation of middle- and back-office systems; support the identification and definition of system and data support models.
- Work with technology partners to conduct functional testing of enhancements and validate data quality across integrated systems.
- Identify gaps in data architecture and contribute to the design of scalable and sustainable solutions.
- Co-lead and facilitate data solution design sessions, translating business requirements into data architecture specifications.
- Advocate for data governance by implementing preventive and detective controls, tracking exceptions, and performing impact analyses.
- Continuously develop domain expertise in investment management practices, data operations, and emerging data technologies.
- Monitor industry trends and evaluate third-party vendors to evolve SWIB’s data ecosystem.
The ideal candidate:
- Bachelor’s degree required, preferably in Data Analytics, Data Science, Finance, or a related field.
- 1+ years of experience in the investment management industry, with a focus on data management, data quality, or data architecture supporting complex, actively managed portfolios is preferred.
- Familiarity with key vendors and platforms such as SimCorp, Markit EDM, FactSet, Bloomberg, BlackRock Aladdin, MSCI, and Charles River is a plus.
- Exposure to cloud technologies, including Snowflake and Microsoft Azure.
- Experience with Informatica or other data quality/governance tools is a plus.
- Understanding of security mastering, data governance frameworks, and industry best practices in investment data management.
- Strong ability to work cross-functionally, translating business needs into effective data solutions.
- Skilled in documenting, communicating, and presenting technical and business concepts to varied audiences.
- Proven track record of designing and delivering data architecture and integration solutions.
- Competitive total cash compensation, based on AON (formerly McLagan) industry benchmarks
- Comprehensive benefits package
- Educational and training opportunities
- Tuition reimbursement
- Challenging work in a professional environment
- Hybrid work environment
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture Azure Data Analytics Data governance Data management DataOps Data quality Engineering Finance Informatica Security Snowflake Testing
Perks/benefits: Career development Competitive pay Relocation support
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