SereneAid - Data Engineer – Senior

Data Engineer is needed in Edmonton, Canada.

Client: SereneAid

Location: Edmonton, AB, ca

Contract: Contract

Job Description

The Senior Data Engineer will primarily support the Digital Regulatory Assurance System (DRAS) program, designing and operating reliable data pipelines and data products. The role focuses on data ingestion, integration, transformation, governance, quality, and delivery of trusted analytics-ready datasets for regulatory, compliance, reporting, and future AI use cases.

Requirements

Must-Have Requirements

• Analytics-ready data solutions, semantic layers, data marts & data products: 3+ years
• Git / GitHub version control: 4+ years
• Azure Storage, SQL, Synapse, networking & secure authentication: 3+ years
• Python / PySpark & SQL Data Engineering: 5+ years
• Azure Databricks & Delta Lake: 3+ years
• AI for code generation, data analysis & automation: 1+ year

Nice-to-Have

• Data requirements analysis / transformation / cleansing / wrangling – 6 years
• Microsoft SQL Server – 6 years
• Microsoft Fabric – 2 years
• Government of Alberta Cloud environment – 1 year
• RESTful API design/integration – 3 years
• ActiveMQ / Azure Service Bus / Message Queueing – 3 years
• Cross-functional software and data product development – 5 years

Contract & Work Schedule

• Hours: 36.25 hours/week
• Daily: 7.25 hours/day
• Schedule: Monday–Friday, 8:15 AM–4:30 PM Alberta Time
• Work Mode: Primarily remote
• Location Requirement: Must work from within Canada
• Onsite: Edmonton meetings approximately 3–4 times per fiscal month or more, as required
• Extension: Up to 6 months

Key Responsibilities

• Design scalable, secure Microsoft Azure data architectures
• Build data ingestion and transformation pipelines using Azure Data Factory, Azure Databricks and Azure Synapse
• Manage Azure Data Lake Storage Gen2
• Integrate data from ServiceNow, geospatial systems and other source systems
• Develop data models and semantic layers
• Build and optimize ETL/ELT workflows using Python, PySpark and SQL
• Develop secure APIs and data services using Azure API Management
• Implement data governance, metadata, classification and lineage
• Apply security controls including RBAC, encryption and data masking
• Monitor and troubleshoot data pipelines and integrations
• Use AI and automation for pipeline development, testing, monitoring and documentation
• Curate standardized, high-quality datasets for advanced analytics and AI