Senior Manager, CX Analytics

SharkNinja•Needham, MA

About The Position

SharkNinja is seeking a Senior Manager, CX Analytics to lead our CX Data capability and build scalable, AI-enabled analytics that power operational excellence across our global Consumer Experience organization. This role sits at the intersection of Contact Center Operations, Voice of Consumer, Quality, and Enterprise Data Engineering. You will combine deep CX domain expertise with strong analytics engineering capability to engineer trusted CX datasets, standardize global CX metrics, enable structured business self-service, and embed AI to accelerate insight generation—in close partnership with our Global Enterprise Data team. This is not a pure dashboard development role. It is a CX-native analytics leadership role focused on building durable, scalable data products that improve speed, clarity, and operational decision-making.

Requirements

8–12+ years in Analytics, with strong CX/Contact Center focus
Deep experience in Contact Center operations, Quality, and Voice of Consumer
Advanced SQL expertise
Strong Snowflake experience
Hands-on dbt model development
Experience operating within a centralised enterprise data platform where domain teams contribute models within shared governance frameworks.
Experience building governed data marts or semantic layers
Experience enabling structured business self-service analytics
Exposure to AI/ML techniques in analytics workflows

Responsibilities

Define and standardize how CX performance is measured globally across: Contact center performance (e.g., AHT, occupancy, forecasting inputs)
Quality assurance frameworks and compliance measurement
Voice of the Consumer analytics
Contact drivers, defect trends, and root cause analysis
Operational backlog and order-related contact dynamics
Cost-to-serve analysis
Design and implement CX domain models and transformations within the enterprise Snowflake and dbt frameworks.
Writing advanced SQL (complex joins, window functions, performance optimization)
Building and maintaining dbt models aligned to enterprise frameworks
Standardizing metric definitions, documentation, and lineage
Refactoring legacy reporting logic into scalable, governed data assets
Ensuring testing, performance reliability, and production-quality code standards
Design curated CX data marts optimized for operational leaders
Build governed semantic layers to prevent metric misinterpretation
Enable leaders to independently answer first-order questions
Reduce ad hoc reporting demand through reusable datasets and clear definitions
Create intuitive analytical pathways rather than complex drill-through journeys
Use AI-assisted SQL and model development to accelerate delivery
Apply anomaly detection techniques to CX KPIs and operational metrics
Automate contact driver clustering and transcript theme extraction
Leverage NLP for Voice of Consumer categorization and insight discovery
Deploy LLM-powered summarization to streamline executive reporting, i.e. Snowflake Intelligence
Evaluate Snowflake-native AI capabilities (e.g., Cortex/COCO) for CX use cases