Senior Data Engineer

Job not on LinkedIn

🕒 August 12

🇨🇦 Canada – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 18%

What it means: the chance that no one is really hiring for this job.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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Pathlion

WebsiteAll Job Openings

- employees

🏛️ Government

💼 Consulting

🏢 Enterprise

Government • Consulting • Enterprise

Pathlion is a professional services firm focused on public-sector digital transformation. It delivers end-to-end project management for ServiceNow implementations and financial-system projects for Ontario government clients, provides senior organizational change management for Alberta consumer-licensing modernization (including AI enablement and adoption), and offers DevOps and automation services for Alberta government digital services. Pathlion’s work centers on program delivery, stakeholder engagement, compliance with government standards and procurement rules, training and adoption, and building CI/CD, monitoring, and production operations for public-sector IT systems.

📋 Description

• Collaborate with business stakeholders and product owners to understand data product objectives, requirements, and success criteria • Design and implement scalable, secure, and high-performance data architecture on Microsoft Azure in cloud-native and hybrid environments • Lead development of data ingestion, transformation, and integration pipelines using Azure Data Factory, Azure Databricks, and Azure Synapse Analytics • Manage data lakes and structured storage solutions using Azure Data Lake Storage Gen2 with efficient access and governance • Integrate data from diverse source systems, including ServiceNow and geospatial systems, using APIs, connectors, and custom scripts • Develop and maintain data models and semantic layers for reporting, analytics, machine learning, and downstream consumption • Build and optimize Python and SQL data workflows for cleansing, enrichment, and advanced analytics in Azure Databricks • Design and expose secure data services and APIs using Azure API Management • Implement metadata management, data classification, and lineage tracking • Ensure privacy and regulatory compliance through role-based access controls, encryption, and data masking • Monitor and troubleshoot data pipelines and integrations for reliability, scalability, and performance • Use AI and automation tools for pipeline development, testing, monitoring, and documentation • Use AI-assisted tools for code generation, optimization, and review • Design and curate standardized, high-quality datasets for advanced analytics and future AI use cases • Perform other duties as needed

🎯 Requirements

• Experience designing scalable, secure, and high-performance data architecture on Microsoft Azure • Experience with cloud-native and hybrid environments • Experience developing data ingestion, transformation, and integration pipelines • Proficiency with Azure Data Factory, Azure Databricks, and Azure Synapse Analytics • Experience managing Azure Data Lake Storage Gen2 and structured storage solutions • Experience integrating ServiceNow and geospatial systems using APIs, connectors, and custom scripts • Experience developing data models and semantic layers for reporting, analytics, and machine learning • Proficiency in Python and SQL • Experience with Azure API Management and secure data services/APIs • Knowledge of metadata management, data classification, and lineage tracking • Knowledge of privacy and regulatory standards including FOIP and GDPR • Knowledge of role-based access controls, encryption, and data masking • Experience monitoring and troubleshooting data pipelines and integrations • Experience using AI and automation tools for data engineering workflows • Experience with AI-assisted code generation, optimization, and review

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