Senior Principal Data Architect

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Principal Data Architect based in Canada.

This is a senior technical leadership role focused on shaping enterprise data architecture across a modern AWS and Databricks Lakehouse environment.

You will define scalable data strategies, models, integration patterns, governance frameworks, and quality standards that support business and technology objectives.

The role combines hands-on architecture with technical leadership, requiring you to personally contribute to data models and pipelines while setting standards for broader teams.

You will work across data engineering, analytics, technology, and business functions to turn complex requirements into reliable, actionable data solutions.

The position offers significant influence over data governance, platform modernization, and the adoption of emerging technologies, including generative AI.

You will mentor engineers, guide technical decisions, and collaborate with distributed teams working across multiple time zones.

This is an opportunity to help build scalable data capabilities while solving complex problems in a collaborative, Agile environment.

Accountabilities

• Define and maintain enterprise data architecture strategies covering data acquisition, archival and recovery, database implementation, modeling, and integration.
• Design scalable, secure data models, data flows, and integration patterns across AWS and the Databricks Lakehouse ecosystem.
• Align data architecture decisions with business objectives, enterprise technology strategy, and long-term scalability requirements.
• Establish data governance frameworks and best practices covering quality, consistency, compliance, metadata, and data discovery.
• Maintain and improve data dictionaries, metadata documentation, and standards that support effective data understanding and usage.
• Provide technical leadership and mentorship to data engineers and other technical team members.
• Communicate architectural strategies, decisions, and best practices to stakeholders at different levels, building alignment and adoption.
• Supervise and review work delivered by contractors and third-party resources to ensure compliance with architectural standards and quality expectations.
• Evaluate and recommend data technologies, tools, and platforms, with an emphasis on AWS-native services and Databricks capabilities.
• Leverage generative AI tools for code generation, data modeling, documentation, and other technical workflows to improve delivery efficiency.
• Lead data architecture initiatives for large-scale projects and digital transformations, remaining hands-on in designing and building models and pipelines.
• Ensure data solutions are delivered within agreed scope and timelines while meeting quality, security, governance, and performance standards.
• Stay current with emerging trends and technologies in data architecture, analytics, cloud platforms, and AI.
• Promote data-driven decision-making and proactively communicate project progress, risks, issues, and major deliverables to leadership and stakeholders.
  
  

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Requirements

• 10+ years of experience in data engineering or data architecture.
• Bachelor’s degree in Computer Science, Information Technology, or a related technical field.
• Strong experience with data engineering practices including profiling, sourcing, cleansing, standardization, transformation, rationalization, linking, and matching.
• Proven experience designing and implementing data models and warehouses using methodologies such as dimensional modeling, star schema, Data Vault, and Kimball within a lakehouse environment.
• Deep understanding of database structures and experience working with multiple database and data warehouse technologies.
• Knowledge of data mining and segmentation techniques.
• Advanced SQL and Python skills, with the ability to translate complex requirements into efficient and maintainable code.
• Hands-on experience with data pipeline orchestration technologies such as Databricks Workflows, AWS Glue, and/or Apache Airflow.
• Experience building data models and dashboards using Databricks SQL and/or Power BI.
• Deep hands-on expertise with the Databricks Lakehouse Platform, including Delta Lake, Unity Catalog, and Databricks SQL.
• Extensive working knowledge of AWS services including S3, EMR, EKS, Glue, Redshift, and Lambda.
• Strong understanding of data governance, quality, security, and regulatory considerations such as GDPR.
• Structured problem-solving skills, with the ability to break down ambiguous challenges and develop effective data architecture solutions.
• Strong leadership, decision-making, communication, and stakeholder management skills.
• Ability to translate business requirements into practical, scalable data models and technical solutions.
• Experience working effectively with remote, distributed teams across multiple time zones and within Agile environments.
• Demonstrated ability to mentor and develop data engineers at different levels of experience.
• Self-motivated, highly organized, proactive, and comfortable managing complex technical initiatives.
• Genuine interest in emerging technologies and a strong passion for solving data-related challenges.
• Proactive use of generative AI tools to accelerate data modeling, coding, documentation, and other technical work.
  
  

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Benefits

• Potential eligibility for additional compensation such as bonuses, commissions, equity, or other incentive programs, where applicable.
• Remote working environment with collaboration across multiple time zones.
• Open PTO policy providing flexibility in how and when time off is taken.
• Quarterly company-wide Days of Disconnect.
• Parental and pawternity leave.
• Quarterly fitness reimbursement through a wellness-focused employee perk.
• Medical, dental, and vision coverage.
• Employee Assistance Program.
• Calm app subscription for employees and up to four eligible dependents over age 16.
• Ongoing learning, training, mentorship, and professional development opportunities.
• Values-focused culture centered on personal growth, collaboration, and an inclusive employee experience.
• Additional employee benefits and programs may be available depending on location and eligibility.
  
  

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!

Why Apply Through Jobgether?

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.