We are seeking a Principal Architect & Data Engineer to serve as the technical visionary and master builder for our next-generation data ecosystem. You will lead the strategy and execution required to unify our current data silos into a high-performance, Federated Enterprise Data Intelligence platform.

In this role, you will balance the "heavy lifting" of massive-scale engineering with the "high-level" strategy of agentic AI and executive-level roadmapping. You will be responsible for creating an environment that provides business units with autonomous "sub-lake" capabilities while maintaining a single, governed enterprise source of truth.

Key Responsibilities

1. Unified Architecture & Engineering

• Data Lakehouse Evolution:Architect the consolidation of disparate storage and compute environments into a unified, high-performance Lakehouse architecture (supporting Iceberg/Delta Lake).

• Agentic Frameworks:Scale and refine our internal agentic platform and registry, ensuring it is robust, model-agnostic, and enterprise-ready.

• Federation & Governance:Design a "Data Mesh" that enables business units to innovate independently within pre-defined guardrails and "Data Zones."

• Data Trust & Observability: Define the standards, contracts, and observability metrics that make structured and unstructured data trustworthy, discoverable, and easy to consume in both batch and near-real-time contexts.

2. Technical Leadership & Mentorship

• Engineering Excellence:Set the global standard for high-performance query analytics, data modeling, and "Zero-Copy" architecture patterns.

• Coach & Develop: Serve as a formal mentor to intermediate and senior data architects and engineers, fostering a culture of technical rigor, automation, and continuous professional development.

• Lead by Influence: Guide technical delivery across federated teams, ensuring decentralized projects align with centralized enterprise architectural standards.

• Technical Direction:Serve as the lead technical resource on the team, heavily influencing decisions regarding tools, implementation, design, and workflows.

3. Executive Communication & Business Alignment

• Sr. Leadership Advisory:Present complex architectural roadmaps, ROI projections, and security risk assessments clearly to the Senior Leadership Team (SLT) and the Board.

• Strategic Mapping:Partner with business leaders to ensure that every data product and ML model directly maps to corporate KPIs, such as Revenue Growth and Operational Efficiency.

Role Requirements & Qualifications

• Experience: 10+ years of professional experience in large-scale data engineering, architecture, and data platform roles, including 1+ years at a Staff or Principal level.

• Languages & Tools:Mastery of Python, SQL, and Spark. Proven experience with workflow orchestration (e.g., Airflow), Infrastructure as Code (Terraform/CloudFormation), and robust CI/CD testing pipelines.

• Cloud Ecosystems:Deep, hands-on expertise in AWS (S3, Glue, Redshift, Bedrock) OR Google Cloud (BigQuery, Vertex AI).

• Advanced Data Patterns:Expert knowledge of federated query engines, semantic layers, and modern "Zero-Copy" data sharing.

Data Governance, Security, & Operations

• Data Operations:Extensive experience operating production data platforms in batch and near-real-time environments with strong lineage, catalogs, and access controls serving as systems of record.

• Data Governance: Proven track record building enterprise data governance, contracts, and quality frameworks for both structured and unstructured data (including metadata standards, classification, and PII detection/redaction).

• Security & Privacy: Ability to define safe-access patterns for AI consumption to prevent sensitive data exposure. Experience enforcing security baselines (encryption, RBAC/ABAC, masking/tokenization) and policy-as-code.

• Cloud Economics:Experience establishing comprehensive frameworks for transparent cost attribution, optimized storage tiering, and advanced metadata tagging. Ability to advise executive leadership on operational efficiency by architecting automated triggers to detect and mitigate budget variances.

AI/ML Depth

• Generative AI:Proven experience architecting RAG (Retrieval-Augmented Generation) patterns, vector readiness concepts (schemas, metadata, provenance), and managing enterprise AI registries.

• Intelligence Orchestration: Experience defining business logic centrally (via semantic modeling) to seamlessly serve both human BI users and programmatic AI agents.

Leadership & Soft Skills

• The "Teacher" Mindset:A documented track record of developing junior and senior talent into high-performing architects.

• Executive Presence:Exceptional ability to simplify complex technical hurdles into strategic business decisions for non-technical stakeholders.

• Architectural Empathy:Ability to successfully navigate the needs of autonomous business units while firmly upholding central IT's security and quality mandates.

Target Base Salary Range: $160,000 CAD - $170,000 CAD

Consistent with Motorola Solutions values and applicable law, we provide the following information to promote pay transparency and equity. Pay within this range varies and depends on job-related knowledge, skills, and experience. The actual offer will be based on the individual candidate.

#LI-MP2
#LI-REMOTE

• 10+ years of experience in data engineering and/or architecture

• AND 5+ years AWS Redshift ecosystem 

• AND 1+ years of experience at a staff or principal level