Data & Analytics Engineer

Robert W. Baird

Milwaukee (WI)

Hybrid

USD 90,000 - 140,000

Full time

14 days+

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Job summary

Robert W. Baird seeks a data & analytics professional in Milwaukee for a hybrid role focused on building scalable data pipelines and analytics-ready datasets. You will partner with stakeholders to drive data-driven decision making and deliver datasets for reporting and insights.

The role emphasizes applying data modeling techniques, profiling data, and ensuring data quality while leveraging existing tools to enable reporting for financial services users.

Qualifications

5 to 7 years delivering data and analytics solutions.

Responsibilities

Contribute to design, develop, and maintain data pipelines ingesting and transforming financial services data.

Skills

Data pipelines

Analytics engineering

SQL

Data modeling

Data profiling

Data quality

Stakeholder collaboration

Tools

SQL Server

Snowflake

Azure SQL Database

Azure Data Lake

T-SQL

Azure Data Studio

Power BI

Alteryx

Job description

Join Robert W. Baird in a hybrid Milwaukee role focused on data and analytics excellence. This position offers a benefits-forward environment with a values-driven culture, opportunities to engage with a multicultural community, and the recognition of a Best Place to Work. You'll design, build, and deliver scalable data pipelines and analytics-ready datasets, partnering with stakeholders to drive data-driven decision making.

Benefits and culture

The role embodies The Baird Way, access to Our Multicultural Community Conference, and the firm’s ongoing commitment to being a Best Place to Work. A hybrid work setup in Milwaukee supports collaboration with teams while maintaining flexibility for focused work.

Responsibilities

Contribute to the design, development, and ongoing maintenance of data pipelines that ingest and transform financial services data.
Apply data modeling techniques, including 3NF and dimensional models, to create analytics-ready datasets.
Analyze and profile source data to understand quality characteristics and support reliable outcomes.
Develop and validate source-to-target mappings and the associated transformation logic.
Implement and test end-to-end data solutions under the guidance of senior engineers.
Adhere to established practices to protect and properly handle sensitive data.
Support data discovery efforts and prototype datasets that integrate multiple data sources.
Leverage existing tools to enable reporting and visualization for financial services users.
Document datasets and transformations to support usability and adoption.
Deliver work incrementally while adapting to changing priorities.
Collaborate with delivery team members, architects, and business partners.
Communicate progress, risks, and dependencies clearly.
Learn and apply Baird data standards, tools, and best practices.
Seek feedback and coaching from senior Data & Analytics Engineers.
Continuously build skills through training, documentation, and hands-on experience.

Requirements

5 to 7 years of experience delivering data and analytics solutions in a collaborative environment.
Experience in data engineering, analytics engineering, business intelligence development, or a related data-focused role.
Strong SQL skills and familiarity with relational database concepts and best practices.
Experience performing data analysis, profiling, validation, and troubleshooting to support reliable data solutions.
Ability to partner effectively with business stakeholders to understand requirements and support analytics needs.
Strong problem-solving skills, intellectual curiosity, and a desire to continuously grow technical expertise.
Experience with databases and platforms such as SQL Server, Snowflake, Azure SQL Database, and Azure Data Lake.
Experience writing queries and developing solutions using SQL, T-SQL, Azure Data Studio, or similar tools.
Familiarity with BI and analytics tools such as Power BI, Alteryx, or comparable platforms.
Working knowledge of data modeling and governance concepts, including 3NF, dimensional modeling, data mapping, data profiling, and data quality practices.
Experience working with common data formats such as CSV, JSON, XML, and Parquet.
Experience in a regulated or data-sensitive environment is preferred.