X - Data Architect - Government of Alberta Pipeline

Sr. Data Architect - GOAPRDJP00000616

Eleventh Floor

9942 - 108 Street

Edmonton

Primarily work remotely but must be available for on-site meetings as required (Meetings may occur up to 3-4 times per fiscal month, but the actual frequency will depend on the specific initiative and will be determined on an on-demand basis.)

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.

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.

Collaborate with cross-functional teams to align data architecture with business requirements, program timelines, and modernization goals.

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

Provide technical leadership and mentorship to data engineers and analysts, promoting best practices in cloud data architecture and development.

Other duties as needed

Must-Have's:

A college or Bachelor's degree in Computer Science or a related field of study.

Hands-on experience managing Databricks workspaces, including cluster configuration, user roles, permissions, cluster policies, and applying monitoring and cost optimization for efficient, governed Spark workloads - 3 years

Experience as a Data Architect in a large enterprise, designing and implementing data architecture strategies and models that align data, technology, and business goals with strategic objectives - 8 years

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 - 4 years

Experience in Github/Git for version control, collaborative development, code management, and integration with data engineering workflows - 4 years

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 - 5 years

Experience in Python (including PySpark) and SQL, applied to developing, orchestrating, and optimizing enterprise-grade ETL/ELT workflows in a large-scale cloud environment - 6 years

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 - 3 years

Nice-to-Have's:

Certification in The Open Group Architecture Framework (TOGAF).

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

Direct, hands-on experience performing business requirement analysis related to data manipulation/transformation, cleansing and wrangling - 8 years

Experience and strong technical knowledge of Microsoft SQL Server, including database design, optimization, and administration in enterprise environments - 8 years

Experience building scalable ETL pipelines, data quality enforcement, and cloud integration using TALEND technologies - 2 years

Experience in data governance, security, and metadata management within a Databricks-based platform - 2 years

Skilled in building secure, scalable RESTful APIs for data exchange, with robust auth, error handling, and support for real-time automation - 3 years

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

Experience working with cross-functional teams to create software applications and data products - 5 years

Experience working with ServiceNow- Azure-based Data Management Platform Integrations - 1 year

Originally posted on Himalayas