About the role

Data and analytics engineer building semantic models, pipelines, and AI-ready infrastructure. Supporting SH/FT’s consultancy work for enterprise marketing and technology clients.

Responsibilities

Partner with business stakeholders to uncover business goals and translate domain needs into unified data engineering solutions, semantic layers, and warehouse architectures
Architect context layers and semantic models for AI/LLM-driven engines and autonomous agents
Design scalable taxonomy and metadata data models using architectures such as Medallion/Multi-layer
Build and maintain deterministic and probabilistic identity resolution models and graph-like bridge tables
Lead integration of complex cross-system datasets
Develop high-performance ingestion and transformation pipelines unifying marketing metadata, CDP activation models, DAM content, and real-time telemetry
Implement enterprise data governance, business glossaries, access controls, and data cataloging
Enable secure self-service analytics and reliable AI execution
Partner directly with clients to understand strategic goals and translate requirements into scalable, warehouse-native infrastructure

5+ years of hands-on experience in data engineering, analytics engineering, or data architecture building production-grade data pipelines and semantic models
2+ years in a client-facing, consultative, or strategic lead role
Ability to run discovery, map business goals to technical architectures, and present solutions to cross-functional stakeholders
Ability to translate non-technical business strategies into clear technical specifications and articulate technical trade-offs
Understanding of agentic AI concepts and how data modeling, semantics, and context layers support autonomous workflows
Hands-on experience designing production pipelines and semantic data models across modern cloud data platforms
Deep expertise in Databricks, Snowflake, or equivalent architectures
Proficiency in SQL, Python/PySpark, data pipeline orchestration, and modern data stack tooling such as dbt
Experience with MarTech, CDPs, reverse ETL tools such as Hightouch or Census, and enterprise platforms such as Salesforce Marketing Cloud and CRMs
Proven experience in multi-dimensional schema design, identity resolution modeling, graph/hierarchical structures, and API payload parsing (nested JSON/REST)
Databricks, Snowflake, or dbt certifications preferred
Ability to manage complex deliverables independently in a distributed, fast-paced environment
Current US or Canada work authorization required
No relocation assistance available