This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Strategic Data & Analytics Engineer (Cloud Data & Agentic Infrastructure) based in Canada.
This role sits at the intersection of data engineering, analytics, enterprise architecture, and emerging AI capabilities.
You will design scalable marketing data models, semantic layers, and cloud-native infrastructure that turn complex business needs into actionable systems.
Working directly with clients and business stakeholders, you will translate strategic objectives into robust technical architectures and data solutions.
You will also help organizations prepare their data ecosystems for agentic AI, LLM-driven applications, and autonomous workflows.
The role spans modern cloud platforms, MarTech ecosystems, identity resolution, data integration, governance, and semantic modeling.
You will operate in a consultative, client-facing environment where technical expertise and business understanding are equally important.
This is an opportunity to shape intelligent data infrastructure for major organizations while contributing to the evolution of AI-ready enterprise architectures.
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.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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