Data Engineer

State of Wisconsin Investment BoardMadison, Wisconsin

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Job Description

Making a Difference

The State of Wisconsin Investment Board (SWIB), founded in 1951, is a premier global investment organization responsible for managing the more than $156 billion of assets of the fully funded Wisconsin Retirement System (WRS), the State Investment Fund and other state funds. Through SWIB’s effective and innovative investment management, WRS remains one of the only fully funded US public pensions. We are the 9th largest public pension fund in the U.S. and the 25th largest public or private pension fund in the world. SWIB is recognized by the investment industry for our teamwork and innovation. SWIB pursues sophisticated global investment strategies across the asset and risk allocation spectrum. Providers across the investment ecosystem seek to partner with SWIB.

Serving more than 691,000 beneficiaries of the WRS, SWIB is a mission-driven organization focused on providing a strong financial future to those who committed their careers to public service. For public employees and the 1,500 Wisconsin employers who contribute on their behalf, we are a trusted partner. Our team innovates continuously to meet the challenges of an evolving investment landscape while growing and protecting the assets of the WRS.

SWIB provides a strong, steady economic pillar for the state of Wisconsin by growing the trust funds under its management, managing risk, and optimizing costs of the long term. We are a mission-driven organization and the participants we serve are our mission. By bringing a disciplined, prudent, and innovative approach to market opportunities, SWIB has been successful in generating required returns and maintaining the trust of the beneficiaries and stakeholders of the funds we oversee.

Home To Top Talent

Our high-performing staff is key to what makes us a premier investment manager. SWIB is committed to investing in talented professionals to implement our robust, sophisticated investment strategies and to keep the organization at the forefront of the investment industry. We encourage innovation and offer professional development opportunities to help staff sharpen and expand their skills. Approximately 61 percent of SWIB’s investment professionals are Chartered Financial Analyst (CFA) charterholders.

Job Description:

About the Team
SWIB’s Technology & Data Division is a highly valued partner to our investment teams and a critical contributor to SWIB's continued growth and success. With approximately 75 employees, the division comprises (a) technology, including business systems analysts, design & development, infrastructure, and information security and governance teams; (b) data, including data science, investment data, investment information architecture, data engineering, and reporting; (c) business integration, change, and coordination; and (d) project management.

As a top asset owner, our technology and data systems address the entire breadth of investments. Our mission-critical technology and data are essential to deliver internally managed equity, fixed income, and hedge funds strategies, and to oversee external managers investing in both private and publicly traded assets. The team also runs the systems to operate and protect our organization. A few of our current key systems include SimCorp, eFront, Charles River, Snowflake, Markit, and FactSet.

Position Overview

In this role, you will be responsible for conceptual, architectural, and technical requirements for all aspects of the company’s enterprise data warehouse initiatives. This role intersects data modeling and data architecture to provide next-generation data lake and data warehouse on the cloud technology (Snowflake). The Data Engineer is responsible for the design, development, and maintenance of the enterprise Data Warehouse.

Essential Activities:

Design, build, and optimize scalable, high-performance data pipelines and cloud-native data warehousing solutions using Snowflake and Azure.

Utilize advanced SQL capabilities (e.g., CTEs, window functions, set operations, performance tuning) to support complex data transformations and integrations.

Develop, schedule, and monitor data workflows using Snowflake Streams, Tasks, and Stored Procedures for real-time and batch ETL/ELT processes.

Implement and maintain CI/CD pipelines using Azure DevOps and GitLab, automating the deployment and testing of data pipeline code and infrastructure.

Work extensively within the Azure ecosystem, leveraging services like Azure Data Factory, Azure Storage, and Azure Functions to build robust data integration solutions.

Develop and maintain dimensional and normalized data models (covering 1NF through 3NF) to support flexible and scalable data architecture.

Create modular, version-controlled data transformation logic that supports automated documentation and testing.

Ingest and transform data from diverse formats (JSON, CSV, Parquet, Avro) and sources, including APIs and both on-premise and cloud systems.

Drive data quality and governance by establishing and enforcing standards, validation rules, and best practices for metadata management and data lineage to ensure the accuracy, consistency, and reliability of enterprise data.

Document technical designs, transformation logic, and architectural decisions clearly and concisely for cross-functional use.

The Ideal Candidate:

Bachelor's degree in computer science, Engineering, Finance, or a related field.

Exposure to the investment or financial services industry.

6–8 years of experience in data engineering, with a strong emphasis on SQL development, ETL/ELT design, and cloud-based data platforms.

2+ years of hands-on experience with Snowflake, including deep knowledge of Streams, Tasks, Procedures, and Snowflake-specific features like virtual warehouses and time travel.

Possesses a strong commitment to data quality and governance, with a proven ability to establish and enforce standards, define validation rules, and implement best practices for metadata management and data lineage to ensure enterprise data is accurate, consistent, and reliable.

Strong understanding of data modeling techniques, including both dimensional and normalized models.

Solid experience working with Azure cloud services for data integration, processing, and orchestration.

Experience with DBT, or similar tool, for transformation logic, modular pipeline development, and automated testing/documentation.

Proven ability to manage multiple data sources and formats across complex architectures.

Strong understanding of CI/CD practices in a data engineering context using Azure DevOps and GitLab.

Optional but Preferred:

Experience with Python for scripting, orchestration, and automation.

Familiarity with Data Vault 2.0, Master Data Management (MDM), or enterprise data quality frameworks.

Snowflake certification (e.g., SnowPro Core or Advanced).

SWIB Offers:

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

The position requires U.S. work authorization.

Pursuant to our Hybrid Remote Work Policy, all staff have the flexibility to work remotely, but are required to have a weekly presence in our offices, the frequency of which is dependent on their distance from office. Staff are not required to reside locally; however, we offer relocation reimbursement to the Dane County area per our policy.

All SWIB employees are subject to SWIB’s Ethics Policy and Personal Trade Approvals Policy. These policies include restrictions on outside business activities and employment and have limits on personal trading. You may request copies of these policies from SWIB’s talent acquisition team and any questions can be answered by SWIB’s compliance team.