Vector Databases Jobs in Milwaukee, WI (NOW HIRING)

At Cotality, we are driven by a single mission-to make the property industry faster, smarter, and more people-centric. Cotality is the trusted source for property intelligence, with unmatched precision, depth, breadth, and insights across the entire ecosystem. Our talented team of 5,000 employees globally uses our network, scale, connectivity and technology to drive the largest asset class in the world. Join us as we work toward our vision of fueling a thriving global property ecosystem and a more resilient society.

Cotality is committed to cultivating a diverse and inclusive work culture that inspires innovation and bold thinking; it's a place where you can collaborate, feel valued, develop skills and directly impact the real estate economy. We know our people are our greatest asset. At Cotality, you can be yourself, lift people up and make an impact. By putting clients first and continuously innovating, we're working together to set the pace for unlocking new possibilities that better serve the property industry.

Job Description:

We are seeking a hybrid or remote Director of Data Engineering & Platforms to lead our data transformation initiatives and establish robust data architecture frameworks. This role reports to the AVP of Cloud Engineering and is responsible for designing, implementing, and maintaining our enterprise data ecosystem across bronze, silver, and gold data layers following Data Mesh and Data Vault methodologies.

This role sits at the intersection of data engineering and AI enablement, where the decisions made in the data layer directly shape the quality of what AI systems can deliver. The ideal candidate will drive technical leadership and strategic direction for our data platform while partnering with Product Management, Data Analytics, Data Systems, Cloud Engineering, and product teams to transform raw data into actionable business intelligence.

Key Responsibilities:

Strategic Leadership & Architecture

• Lead the development and implementation of our data engineering strategy, architecture roadmap, and technical standards

• Oversee the design and evolution of our data ecosystem utilizing Data Vault methodologies and Data Mesh principles

• Establish governance and quality frameworks across Bronze (raw), Silver (transformed), and Gold (consumption-ready) data layers

• Partner with Product Management to align data platform capabilities with business objectives and market demands

• Drive the technical roadmap for data integration, transformation, and delivery systems, with explicit milestones for AI readiness

Technical Direction & Delivery

• Provide technical leadership and oversight for the data engineering team, ensuring best practices in data pipelines, transformations, and delivery

• Oversee the design and implementation of Snowflake data architecture including warehousing, marts, and access patterns optimized for both BI and AI workloads

• Direct the development of robust ETL/ELT processes using Matillion, Python-based pipeline frameworks, and other modern data integration tools

• Guide the implementation of data quality monitoring, lineage tracking, and metadata management

• Establish standards for data modeling, transformation logic, and performance optimization

AI Data Infrastructure

• Partner with AI/ML and product engineering teams to ensure the data layer supports LLM-powered applications reliably and at scale

• Provide architectural direction for retrieval and grounding pipelines, including vector stores, embedding workflows, and hybrid search infrastructure

• Define standards for data preparation for AI, covering metadata enrichment, context optimization, and semantic indexing

• Build observability into AI data flows and monitor for drift and retrieval quality degradation

• Guide the team's evaluation and adoption of emerging AI-native data tools, including vector databases and LLM orchestration frameworks

AI Governance & Risk

• Establish governance frameworks for AI data use, including data lineage into models, PII controls upstream of LLM consumption, and output auditability

• Define the organization's standards for acceptable AI data quality thresholds and remediation workflows

• Partner with Security and Compliance to ensure AI data pipelines meet regulatory and privacy requirements

Team Leadership & Development

• Build, mentor, and lead a high-performing data engineering team with strong core data engineering fundamentals and a growing fluency in modern AI infrastructure

• Collaborate cross-functionally with Product Management, Data Analytics, Data Systems, Cloud Engineering, and product teams

• Foster a culture of innovation, continuous improvement, and technical excellence where AI is a tool the team uses daily, not a project they hand off

• Develop talent through coaching, training, and career development opportunities, with an emphasis on AI-era skills including Python, vector search, and agentic pipeline concepts

• Promote adaptive methodologies and DevOps practices within the data engineering discipline

BI & Analytics Enablement

• Oversee the technical implementation of Power BI reporting solutions and analytics platforms

• Ensure data pipelines efficiently support BI reporting needs and business intelligence requirements

• Partner with Data Analytics teams to optimize data structures for analytical workloads

• Guide the design of data models that enable self-service analytics and reporting

• Establish patterns for efficient and secure data access across the organization

Innovation & Future-State Planning

• Evaluate emerging technologies and methodologies for potential integration into our data platform, with particular attention to AI/ML tooling and agentic workflow frameworks

• Lead proof-of-concepts and pilots for innovative data solutions, including AI-powered pipeline automation and LLM-grounded analytics

• Develop the technical foundation to support advanced analytics and machine learning initiatives

• Guide the evolution of our data architecture to support real-time and streaming use cases

• Stay current with industry trends and incorporate best practices into our data ecosystem

Job Qualifications:

• Bachelor's degree from an accredited institution or equivalent professional experience with demonstrated capability

• 8+ years of progressive experience in data engineering, data architecture, or related technical roles

• 5+ years of leadership experience managing data engineering teams and initiatives

• Extensive experience with modern data platforms, particularly Snowflake and cloud-based data solutions

• Deep understanding of data modeling techniques including Data Vault, dimensional modeling, and Data Mesh concepts

• Hands-on experience with ETL/ELT tools like Matillion and data integration patterns

• Strong knowledge of SQL Server, Cosmos DB, and database technologies

• Experience with Power BI or similar BI platforms and understanding of reporting architectures

• Proven track record implementing data governance, quality, and metadata management solutions

• Experience partnering with product teams and translating business requirements into technical solutions

• Demonstrated interest in AI/ML data infrastructure, whether through independent projects, coursework, or applied experimentation

• Ability to engage credibly with engineers building LLM-powered systems and make sound architectural decisions without being the implementer

Preferred Qualifications:

• Bachelor's or master's degree in computer science, Information Systems, or a related field

• Proficiency in Python and experience with Spark or other data processing frameworks

• Knowledge of CI/CD practices and DevOps for data pipelines

• Has independently explored or prototyped with vector databases, RAG pipelines, or LLM grounding concepts

• Familiarity with LLM orchestration frameworks such as LangChain or LlamaIndex

• Exposure to agentic workflow concepts and the data contracts they require

• Experience with real-time data integration and streaming architecture

• Background in implementing data security and privacy controls

• Understanding of API design and microservices architectures

• Experience in insurance, financial services, or real estate industries

#LI-Remote

Annual Pay Range:

Application Window:

This opportunity is expected to remain posted through the date identified below, subject to business needs.

Thrive with Cotality

At Cotality, we offer more than just a job, we provide a benefits experience designed to support your whole self. From a flexible working model to competitive time off and standout health coverage with meaningful perks and growth opportunities, our package is built to help you thrive at work and in life.

Highlights, depending on role classification, include:

• Time off: Generous PTO and 11 paid holidays, plus well-being and volunteer time off.

• Family Support: Up to 16 weeks of fully paid parental leave and a baby stipend.

• Health: Multiple medical plan options with mental health and wellness support offerings.

• Retirement: 401(k) with company match and vesting after one year.

• Financial Perks: $400 annual well-being stipend and tuition assistance up to $5,250.

• Extras: Recognition Rewards, Referral bonuses, exclusive discounts and more!

Please note, Qualifications, locations and experience of the individual ultimately selected for the position may impact the final actual offered compensation, which may vary from the posted range

Cotality is an Equal Opportunityemployer committed to attracting and retaining thebest-qualified people available, without regard torace, color, religion, national origin, gender, sexualorientation, gender identity, age, disability or statusas a veteran of the Armed Forces, or any other basisprotected by federal, state or local law. Cotalitymaintains a Drug-Free Workplace.

Cotality is fully committed to a work environment that embraces everyone's uniquecontributions, experiences and values. We offer anempowered work environment that encouragescreativity, initiative and professional growth andprovides a competitive salary and benefits package. We are better together when we support and recognize our differences.

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