Lead Data Architect - Cloud & Analytics

Continuus Technologies LLC

Germantown, WI, United States

8 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

8 years minimum

Working hours

Regular working hours

Job source

www.juju.com

Tech stack

FactSet Data Analysis Cloud Computing Data Architecture Information Engineering Data Infrastructure Cloud Services Workflow Management Systems Enterprise Data Management Cloud Platform System Snowflake Data Strategy

+1 more

Data Pipelines

Job description

We’re looking for a Lead Data Architect to design and evolve a modern cloud data platform supporting investment and analytics workflows. This role combines hands-on architecture with strategic leadership and is ideal for someone who has successfully led enterprise data modernization initiatives.

You’ll partner with business and technical teams to shape data strategy, guide platform decisions, and build scalable solutions that support critical decision-making. This is a highly visible role requiring both technical depth and the ability to influence stakeholders. What You’ll Do

Architect scalable cloud data platforms for analytics and operational use
Design enterprise data models and data pipelines
Lead modernization of legacy data environments
Evaluate and integrate data vendors and platforms
Partner with business stakeholders to translate requirements into technical architecture
Establish architecture standards, governance, and best practices
Mentor engineers and elevate technical capabilities across teams
Drive adoption of modern data tools and frameworks

Requirements

8+ years of experience in data engineering, architecture, or platform engineering
Strong hands-on experience with Snowflake or similar cloud data platform
Experience designing and implementing enterprise data architectures
Proven track record leading modernization or transformation initiatives
Strong communication skills and ability to explain technical concepts to non-technical stakeholders
Experience working with complex or high-volume data environments

Preferred Experience

Exposure to financial, investment, or analytical data ecosystems
Experience integrating market or enterprise data vendors (FactSet, Bloomberg, Refinitiv, etc.)
Familiarity with front office or operational analytics workflows
Experience with dbt, orchestration tools, or modern data stack frameworks
Vendor/platform evaluation or selection experience
Background mentoring engineers or leading technical initiatives