The Challenge
Baird is scaling its data capabilities and needs someone who speaks both data engineering and marketing. You'll own the pipelines and models that turn raw marketing data into insights that drive campaign decisions and customer strategy.
Your Mission
Master Baird's data stack, standards, and marketing data sources; complete onboarding with SQL Server and Snowflake environments
Own 2-3 marketing data pipelines end-to-end: from requirements gathering through validation and documentation
Build trust with Marketing stakeholders by delivering first campaign performance datasets and attending weekly sync calls
Contribute to dimensional modeling work for customer engagement and channel analytics use cases under senior engineer guidance
Lead design and deployment of source-to-target mappings for 3+ marketing data sources with documented transformation logic
Develop reusable data models and metrics for campaign reporting, segmentation, and funnel analysis
Mentor junior engineers or analysts on Baird's data profiling and validation practices; reduce data quality incidents by 20%
Deliver incrementally on backlog; ship at least one self-scoped analytics enablement project (e.g., discovery dataset or BI prototype)
KPIs You'll Own
Pipeline uptime & data freshness
Percentage of scheduled marketing data pipelines running on-time with <4hr latency.
Data quality score
Tracked through validation tests; target is 98%+ accuracy on critical marketing datasets.
Stakeholder adoption
Number of Marketing users actively querying your datasets and analytics models per month.
Documentation coverage
% of datasets and transformations with complete technical and business documentation.
Tools & Stack
Your Team
Your Manager
Senior Data & Analytics Engineer or Data Engineering Lead (not specified)
Current Team
Data & Analytics team within IT; cross-functional with Marketing, Architecture, and Delivery
New role to support growing marketing analytics demand
The Package
Salary
$95K-$125K base
Remote
On-site in Milwaukee, WI; full-time
Benefits & Perks
Company Intelligence
Baird is a private investment bank and wealth management firm scaling its data and analytics capabilities. They're investing heavily in modern data platforms and analytics engineering to enable better business decisions across marketing, risk, and operations.
Culture
Collaborative, structured around best practices; emphasis on documentation, data quality, and learning
Is This Role For You?
- You have 5-7 years hands-on experience building and maintaining data pipelines in SQL, dbt, or similar tools
- You enjoy translating messy marketing data requirements into clean, queryable models that analysts and stakeholders actually use
- You're comfortable working on-site in Milwaukee and thrive in collaborative cross-functional teams
- You want to deepen your data engineering skills while staying close to business impact and marketing use cases
- You value clear documentation, code quality, and continuous learning from senior engineers
- You need full remote flexibility-this role is 100% on-site in Milwaukee
- You're looking for a pure data scientist or analytics role; this is primarily engineering-focused with hands-on pipeline and ETL work
- You prefer fast-paced startup environments over structured, standards-driven enterprise data practices
Interview Process
Initial screening
Phone conversation with recruiter about experience, location, and role expectations
Technical interview
SQL and data modeling scenarios with a senior Data & Analytics Engineer; discuss past pipeline work and problem-solving approach
Stakeholder conversation
Chat with a Marketing Analytics lead or business stakeholder to assess communication skills and curiosity about marketing data needs
Leadership interview
Conversation with hiring manager or Data Engineering leadership on team fit, growth mindset, and alignment with Baird standards
Ready when you are
Interested in this role?
Apply now and hear back within days, not weeks.
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About Data & Analytics roles
Data & analytics professionals in marketing transform raw data into actionable insights. They build dashboards, run attribution analysis, design experiments, and help marketing teams make data-driven decisions.