Business Analytics Architect

Muck Rack is the leading SaaS platform for public relations and communications professionals. Our mission is to enable organizations to build trust, tell their stories, and demonstrate the unique value of earned media. Muck Rack’s AI-powered, comprehensive, and integrated platform streamlines the PR workflow to help businesses generate positive media coverage, monitor mentions to manage brand reputation, and analyze PR’s impact on business outcomes. By combining media database, monitoring, and reporting into one dynamic platform, we empower teams to collaborate seamlessly, pitch effectively, and analyze results faster and more efficiently.

Founder-controlled, fully distributed, and growing sustainably, Muck Rack has received several awards for its unparalleled culture and product from organizations like Inc., Quartz, G2, and BuiltIn. We value resilience, transparency, ownership, and customer devotion, and infuse these values into everything we do.

We’re looking for a collaborative, self-motivated Analytics Architect to join our Business Data Analytics team.

Reporting to the VP, Analytics, you’ll serve as the lead architect for Business Data Analytics, defining and driving an AI-first data and analytics architecture that modernizes our analytics platform and enables new ways for teams to access and interact with data.

You’ll establish the technical blueprint for a modern data analytics stack supporting Data Ingestion to Snowflake / Databricks, Data Modeling / Semantic Layers (dbt, Python, SQL), Natural Language Analytics (Agents), Data Activation (rETL, System to System), and Self-Service Analytics (BI Tools). You’ll collaborate across Data Science, Engineering, Product, and Revenue Operations to establish scalable architecture, integration patterns, governance, and engineering practices that enable trusted data and AI-powered analyticsacross the business.

What You’ll Do

Define and drive the target architecture for an AI-first enterprise data and analytics platform, establishing the technical direction and patterns needed to modernize and consolidate the analytics technology stack

Architect scalable data infrastructure, ingestion and transformation frameworks, storage models, and integration patterns across Snowflake, Databricks, dbt, Python, SQL, and related systems

Design governed semantic data layers and the supporting architecture for AI agents, natural language querying, conversational analytics, and other AI-powered data experiences

Establish architecture patterns for retrieval, APIs, and integrations that allow AI agents and applications to securely discover, understand, and interact with trusted enterprise data

Lead the evolution of data governance, security, privacy, access control, and compliance patterns across the analytics stack, balancing accessibility with appropriate safeguards

Establish and champion engineering standards for data modeling, testing, observability, CI/CD, documentation, deployment, and system integration, improving the reliability and maintainability of the analytics platform

Provide technical leadership and mentorship to the Analytics Engineers on the team

To Be Set Up for Success in This Role, You’ll Need to Have

7+ years of experience designing and evolving modern data and analytics architectures, including responsibility for architectural decisions that span multiple systems, teams, or business use cases

Deep experience with modern cloud data platforms and analytics engineering practices, including Snowflake, Databricks, dbt, Python, and SQL

Experience designing scalable data models, transformation pipelines, semantic or metrics layers, and integration patterns that enable trusted self-service analytics

Experience architecting or implementing AI-enabled data systems, such as natural language analytics, AI agents, Retrieval-Augmented Generation (RAG), vector search, or related LLM-powered data workflows

Strong knowledge of enterprise data governance, security, privacy, access control, and data quality practices, with experience translating those requirements into practical technical architecture

Experience establishing engineering practices such as automated testing, CI/CD, observability, version control, and reliable deployment patterns for data and analytics systems

Demonstrated ability to set technical direction, evaluate complex architectural trade-offs, and influence decisions across teams without relying on direct authority

Strong communication skills with the ability to translate complex data and AI architecture into clear decisions, standards, and technical direction for both technical and business partners

If Any of the Below Also Describe You, This Could Be an Exciting Opportunity

You’ve helped modernize or consolidate a fragmented enterprise data ecosystem into a more cohesive modern data stack

You’ve designed semantic or metrics layers specifically to support AI-powered, conversational, or self-service analytics

You have experience taking AI agents or RAG-based data applications from architecture through production implementation

You’ve developed reusable frameworks, standards, or platform capabilities that increased the effectiveness of analytics and engineering teams

You enjoy mentoring engineers and raising technical standards while remaining an individual contributor

You’re comfortable operating in ambiguous technical environments where the architecture is still being defined and your decisions will influence how teams build for years to come

In Addition, We’re Always Looking for Candidates Who

Approach architecture pragmatically, balancing immediate business needs with scalability, maintainability, security, and long-term platform health

Build alignment across technical and non-technical teams and communicate architectural decisions and trade-offs clearly

Take ownership of ambiguous, complex problems and create clarity and actionable technical direction

Look for opportunities to create reusable systems, standards, and patterns that increase the effectiveness of other teams

Share knowledge generously and mentor teammates through complex technical and architectural challenges

Proactively incorporate AI tools into day-to-day work to improve productivity and accelerate delivery

Interview Overview

Below you'll find an outline of the interview plan for this role. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision.

30 min interview with a member of our Talent Team

A 1 hour zoom interview with the hiring manager

Peer interviews with several team members

Skills Assessment

Executive interviews

30-minute Bar Raiser

Travel & Team Engagement Expectations

This role requires up to 10% travel for team collaboration, customer engagements, and company events. As part of our commitment to building strong connections across our fully distributed team, attendance at our annual company offsite (typically held in Mexico) is expected.

Salary

The anticipated salary range for this role in Ireland is €110,000–€130,000 annually, depending on experience.

The anticipated salary for this role in United Kingdom is £130,000–£150,000, depending on experience.

Individual compensation decisions are based on a number of factors, including experience level, skillset, and balancing internal equity relative to peers at the company. We expect the majority of the candidates who are offered roles at our company to fall healthily throughout the range based on these factors. We recognize that the person we hire may be less experienced (or more senior) than this job description as posted. If that ends up being the case, the updated salary range will be communicated with you as a candidate.

Why Muck Rack?

Remote Work, Forever

Fully distributed team with a permanent remote setup

Home office stipend,