Strategic Data & Analytics Engineer (Cloud Data & Agentic Infrastructure)

Accountabilities:

• • Partner with business leaders and stakeholders to understand strategic objectives, uncover complex domain requirements, and translate them into scalable data engineering and architecture solutions.
  • Design and maintain enterprise marketing data models, semantic layers, ontologies, and warehouse-native architectures that support analytics, activation, and AI use cases.
  • Architect semantic context layers and data models designed to support LLM-powered applications, autonomous AI agents, tool use, context retrieval, and agentic workflows.
  • Build scalable multi-layer data architectures, including controlled taxonomies, classification hierarchies, standardized metadata, asset tags, and enterprise business glossaries.
  • Develop deterministic and probabilistic identity resolution models and graph-oriented structures to connect customer identities across CRM records, devices, digital touchpoints, and other data sources.
  • Lead cross-system integrations and develop high-performance ingestion and transformation pipelines connecting cloud warehouses, CDPs, MarTech platforms, DAM systems, activation tools, and real-time telemetry.
  • Work with platforms such as Databricks, Snowflake, Salesforce, and Hightouch to create reliable data foundations for analytics and marketing activation.
  • Implement data governance, access controls, cataloging, metadata management, and data-quality practices to support secure self-service analytics and dependable AI execution.
  • Communicate architectural decisions, technical trade-offs, and recommended solutions clearly to executives, business stakeholders, and cross-functional technical teams.
  • Independently manage complex client deliverables within a distributed, fast-paced consulting environment.
  • Stay current with developments in cloud data platforms, modern data stacks, MarTech, semantic technologies, and agentic AI, identifying opportunities to improve client solutions.

  Requirements:

  • 5+ years of hands-on experience in data engineering, analytics engineering, or data architecture, with a track record of building production-grade data pipelines and semantic models.
  • 2+ years of experience in a client-facing, consultative, or strategic leadership capacity, including discovery, requirements gathering, solution design, and stakeholder presentations.
  • Strong consultative and business-oriented mindset, with the ability to translate ambiguous business strategies into clear technical requirements and architectures.
  • Hands-on expertise with modern cloud data platforms, particularly Databricks, Snowflake, or equivalent technologies.
  • Advanced proficiency in SQL, Python/PySpark, data pipeline orchestration, and modern data stack tools such as dbt.
  • Strong understanding of data modeling, including dimensional models, multi-layer or Medallion architectures, identity resolution, hierarchical and graph-like structures, and nested JSON/REST API payloads.
  • Experience with MarTech, Customer Data Platforms, reverse ETL technologies such as Hightouch or Census, CRM ecosystems, and enterprise marketing platforms.
  • Practical understanding of agentic AI, LLM context retrieval, tool use, autonomous workflows, and the implications of AI on data modeling and semantic infrastructure.
  • Strong knowledge of data governance, metadata management, business glossaries, data cataloging, access controls, and enterprise data quality practices.
  • Excellent written and verbal communication skills, with the ability to explain complex technical concepts and trade-offs to both technical and non-technical audiences.
  • Ability to work autonomously, prioritize effectively, and deliver high-quality results in a remote and distributed environment.
  • Professional Data Engineer or Analytics Engineer certifications in Databricks or Snowflake are preferred.
  • Relevant certifications such as Databricks Certified Data Engineer Professional, Databricks Certified Analytics Engineer, SnowPro Core, SnowPro Advanced Architect, or dbt Cloud Developer Certification are advantageous.
  • Current authorization to work in Canada is required.

  Benefits:

  • Competitive compensation aligned with experience, skills, certifications, and scope of responsibilities.
  • For reference, the published U.S. compensation range for the role is US$120,000–$140,000 per year; Canadian compensation may vary based on location and applicable employment terms.
  • Fully remote work flexibility.
  • Medical, dental, and vision benefits, where applicable.
  • Short-term and long-term disability coverage.
  • Life and AD&D insurance.
  • Flexible Paid Time Off.
  • Additional ancillary benefits and employee perks.
  • Collaborative culture that values diverse perspectives, innovation, and forward-thinking ideas.
  • Opportunity to work on high-impact data, marketing technology, cloud, and AI initiatives for enterprise clients.
  • Exposure to emerging agentic AI and modern cloud data architectures.
  • Professional environment that encourages autonomy, strategic thinking, and measurable client impact.
  • Accessibility accommodations are available throughout the selection process upon request.
  • No relocation assistance is currently available.