Forward Deployed Data Architect

Job not on LinkedIn

🔥 6 minutes ago

🇨🇦 Canada – Remote

💵 $160k - $190k / year

⏰ Full Time

🟠 Senior

🔴 Lead

🚰 Data Engineer

👻 Ghost score 24%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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ShyftLabs

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤖 Artificial Intelligence

💼 Consulting

🏢 Enterprise

Artificial Intelligence • Consulting • Enterprise

ShyftLabs is a company that specializes in delivering data and AI solutions to enterprises. They offer a range of services, including consulting, prototyping, solutions, platform scaling, and operations to help businesses navigate their data journey and leverage AI for transformative impact. ShyftLabs focuses on empowering organizations with advanced data analytics, AI capabilities, and secure data infrastructure to drive real value and optimize operations across the enterprise. They partner with clients throughout the entire lifecycle of data and AI needs, ensuring efficient and impactful integration of AI solutions into existing workflows. With expertise in cloud platform services and a commitment to secure, optimal performance, ShyftLabs delivers tailored solutions for strategic data and AI transformation.

📋 Description

• Work directly with client stakeholders to understand business objectives, technical requirements, existing data environments, and architectural challenges • Design and recommend modern data platform architectures using Azure Databricks, Delta Lake, and cloud-based data engineering technologies • Facilitate technical workshops, discovery sessions, and architecture reviews • Develop, validate, and review data engineering solutions using SQL, Python/PySpark, Apache Airflow, and dbt Core • Establish standards for ingestion pipelines integrating APIs, databases, files, and cloud data sources • Define reusable architectural patterns, implementation guidelines, and engineering best practices • Design and guide Bronze, Silver, and Gold medallion data layers • Establish practices for Unity Catalog, data access controls, lineage, semantic modeling, data discoverability, and governance • Review partner and engineering team deliverables, including architecture designs, code, data models, and pipelines • Define standards for data validation, automated testing, pipeline monitoring, error handling, and operational readiness • Guide Git workflows, automated testing, CI/CD pipelines, and controlled deployments • Evaluate performance, processing efficiency, scalability, and cloud consumption for optimization • Encourage AI-assisted development tools and specification-driven engineering practices • Provide technical direction and coordinate client stakeholders, internal engineers, and external technology partners • Communicate architectural decisions, trade-offs, dependencies, risks, and recommendations • Maintain architectural ownership from discovery and solution design through implementation, deployment, and optimization

🎯 Requirements

• 8+ years of overall experience in data engineering, data architecture, or related technical roles • Proven experience in a client-facing technical role, such as Data Architect, Solutions Architect, Technical Consultant, or Lead Data Engineer • Strong hands-on expertise with Azure Databricks • Deep understanding of Delta Lake • Experience with Unity Catalog, including data governance, access controls, lineage, and enterprise data management • Strong proficiency in SQL and Python/PySpark • Hands-on experience with Apache Airflow and dbt Core • Experience designing ingestion pipelines across APIs, relational databases, files, and other enterprise data sources • Familiarity with Lakeflow Connect and Auto Loader • Strong understanding of Medallion Architecture, data products, semantic modeling, and data quality frameworks • Experience with CI/CD, Git, automated testing, monitoring, and production data pipeline management • Ability to review and challenge technical architectures, code, data models, and engineering deliverables • Experience translating business requirements into technical specifications, architectural designs, and implementation roadmaps • Ability to evaluate technical trade-offs and communicate recommendations clearly • Experience working with external technology partners, third-party delivery teams, or distributed engineering organizations • Familiarity with AI-assisted development tools and spec-driven development practices • Strong communication, presentation, stakeholder management, and problem-solving skills • Ability to manage competing priorities, navigate ambiguity, and build trusted client relationships