A

Intermediate Data Engineer - Azure, Databricks, Synapse (Remote, Canada Only)

ALL JANS Canada
Remote
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AI Summary

Design, build, and maintain scalable data pipelines on Azure. Ingest, transform, and integrate data from diverse sources. Ensure data quality, governance, and security. Support regulatory functions for Government of Alberta's Digital Regulatory Assurance System.

Key Highlights
1-year contract, $60 CAD/hr (incorporation required)
Remote work within Canada, standard hours 08:15 - 16:30 Alberta time
Must have right to work in Canada, no visa sponsorship offered
Key Responsibilities
Design and implement scalable data architecture on Microsoft Azure
Develop and manage data ingestion, transformation, and integration pipelines
Work with data lakes, structured storage, and data models
Integrate data from diverse sources including ServiceNow and geospatial systems
Ensure data governance, security, and compliance with regulatory standards
Technical Skills Required
Azure (Databricks, Synapse, Data Factory, Data Lake) Python (including PySpark), SQL Data governance, security, and metadata management
Benefits & Perks
Remote work within Canada
Standard work hours

Job Description


Role: Data Engineer - Intermediate (REMOTE) #JP975

 

! STRICTLY DO NOT APPLY IF YOU'RE NOT IN CANADA AND HAS NO WORK AUTHORIZATION !

! PLEASE READ BELOW ENTIRE MESSAGE !

 

(NOTE: We are considering Canadian Citizen and PR holders. For the candidate who are on Work Permits and awaiting PR invitation, we don’t provide T4 because this is contract job and the rate we provide is for incorporation. Hence, PR points are not applied, for example: if you’re applying PR under CEC class.)

 

 

[Client]: Government of Alberta


[Contract length]: 1 Year contract


Incorporation Rate: $60 CAD/hr (Canada or Provincial incorporation is a MUST)

 

[Respond by]: 27 - July - 2026

 

[Anticipated Interviews dates]:

• will be held between 27-31 July, 2026; this is an estimate only.

 

[Scoring Methodology]:

Financial/Pricing: 20% 

Resource Qualifications: 20% 

Interview Process: 60%


[SUBMISSION MUST INCLUDE]:

• RESUME

• ALL REQUIRED EXPERIENCE MUST BE DESCRIBED IN RESUME UNDER THE JOB/PROJECT WHERE EXPERIENCE WAS ATTAINED.

• EACH JOB/PROJECT MUST CONTAIN THE TERM OF THE JOB/PROJECT IN THE FORMAT MMM/YYYY to MMM/YYYY.

• THREE REFERENCES, FOR WHOM SIMILAR WORK HAS BEEN PERFORMED, MUST BE PROVIDED. THE MOST RECENT REFERENCE SHOULD BE LISTED FIRST. REFERENCE CHECKS MAY OR MAY NOT BE COMPLETED TO ASSIST WITH SCORING THE PROPOSED RESOURCE.

 

[MUST HAVE WORK EXPERIENCE]:

1+ years of Use of AI-Experienced in using AI for code generation, data analysis, automation, and enhancing productivity in data engineering workflows.

7+ years of Experience building scalable data pipelines with Azure Databricks, Delta Lake, Workflows, Jobs, and Notebooks, plus cluster management. Extending solutions to Synapse Analytics and Microsoft Fabric is a plus.

7+ years of Experience designing data solutions for analytics-ready, trusted datasets using tools like Power BI and Synapse, including semantic layers, data marts, and data products for self-service, data science, and reporting

7+ years of Experience in data governance, security, and metadata management within a Databricks-based platform.

7+ years of Experience in Github/Git for version control, collaborative development, code management, and integration with data engineering workflows.

7+ years of Experience with Azure services (Storage, SQL, Synapse, networking) for scalable, secure solutions, and with authentication (Service Principals, Managed Identities) for secure access in pipelines and integrations

7+ years of Experience in Python (including PySpark) and SQL, applied to developing, orchestrating, and optimizing enterprise-grade ETL/ELT workflows in a large-scale cloud environment.

7+ years of Direct, hands-on experience performing business requirement analysis related to data manipulation/transformation, cleansing and wrangling.

7+ years of Experience and strong technical knowledge of Microsoft SQL Server, including database design, optimization, and administration in enterprise environments.

7+ years of Experience extending or integrating data solutions with Azure Synapse Analytics and Microsoft Fabric (Lakehouse, Warehouse, Semantic Models).

1+ years of Direct experience building data products in Government of Alberta cloud environment

6+ years of Experience building scalable ETL pipelines, data quality enforcement, and cloud integration using TALEND technologies.

6+ years of Skilled in building secure, scalable RESTful APIs for data exchange, with robust auth, error handling, and support for real-time automation.

6+ years of Experience working with cross-functional teams to create software applications and data products.

1+ years of Experience working with ServiceNow- Azure based Data Management Platform Integrations.

3+ years of Experience in Message Queueing Technologies, implementing message queuing using tools like ActiveMQ and Service Bus for scalable, asynchronous communication across distributed systems.



 

[Job Description]:

Project Name:  

Digital Regulatory Assurance System

 

Scope: 

Modernization initiatives across the Government of Alberta are fundamentally changing how ministry users collect, manage, analyze, and use data as legacy systems are transformed into modern Data Management and Geospatial Platforms. This shift requires dedicated analytical capacity to ensure that the value of modernized data assets is fully realized.

DRAS is a Government of Alberta regulatory transformation initiative led by Environment and Protected Areas (EPA) to modernize, digitize, and streamline environmental and natural resource regulatory processes. DRAS supports the full regulatory lifecycle, from application and authorization to monitoring, compliance, remediation, and closure through a single, consolidated digital platform

As DRAS development continues, the volume, variety, and complexity of structured data continue to grow, creating a sustained need for dedicated data engineering and data product expertise. The Data Product Analyst role is critical to ensuring that modernization delivers tangible business value. This role will design, build, and operate reliable data pipelines that ingest and integrate data into the DMP, apply standardized transformations, enforce data quality and governance controls, and produce trusted, analytics‑ready datasets that support regulatory oversight, compliance monitoring, and evidence‑based decision‑making aligned with DRAS objectives.

This position will primarily support the Digital Regulatory Assurance System (DRAS) program, where high quality, timely analytics are essential to regulatory and compliance functions. As data and analytics maturity increases, the role may be expanded to support additional enterprise data

[DUTIES]: 

Design and implement scalable, secure, and high-performance data architecture on Microsoft Azure, supporting both cloud-native and hybrid environments. 

Lead the development of data ingestion, transformation, and integration pipelines using Azure Data Factory, Azure Databricks, and Azure Synapse Analytics. 

Work with the Data Architect and manage data lakes and structured storage solutions using Azure Data Lake Storage Gen2, ensuring efficient access and governance. 

Integrate data from diverse source systems including ServiceNow, and geospatial systems, using APIs, connectors, and custom scripts. 

Develop and maintain robust data models and semantic layers to support operational reporting, analytics, and machine learning use cases. 

Build and optimize data workflows using Python and SQL for data cleansing, enrichment, and advanced analytics within Azure Databricks. 

Design and expose secure data services and APIs using Azure API Management for downstream systems. 

Implement data governance practices, including metadata management, data classification, and lineage tracking. 

Ensure compliance with privacy and regulatory standards (e.g., FOIP, GDPR) through role-based access controls, encryption, and data masking. 

Monitor and troubleshoot data pipelines and integrations, ensuring reliability, scalability, and performance across the platform. 

Utilize AI and automation tools to streamline data engineering workflows, including pipeline development, testing, monitoring, and documentation. 

Leverage AI-assisted tools for code generation, optimization, and review to improve development efficiency and code quality. 

Design and curate standardized, high‑quality datasets that are suitable for advanced analytics and future AI use cases.  


[Equipment Requirements]:

• Resource will require own equipment/laptop. The resource must provide their own computer and related equipment. The computer's operating system must be a modern version of Windows or macOS that is compatible with Azure Virtual Desktop (AVD) and other related software for remote access. Windows is preferred due to better compatibility. AVD and related software will be installed on the resource's computer.

 

[Working Hours]:

• Standard Hours of work are 08:15 – 16:30 Alberta time, Monday through Friday excluding holidays observed by the Province

• Work must be done from within Canada, due to network and data security issues.

• It is anticipated the role will be 100% remote, however in the event of an onsite meeting, the GoA does not pay for travel to attend on-site meetings, nor any expenses related to relocation, commuting, housing/accommodation, food/drink.

 

[Notes on Location]:

  • • Resource will work remotely.

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