Job closedPosted a month ago

Upstaff - Data Engineer – Senior

Data Engineer
Open to offers Edmonton, Canada
Twine JobsVerified
Stretford, United Kingdom · Organization
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Data Engineer is needed in Edmonton, Canada.

Client: Upstaff

Location: Edmonton, AB, ca

Contract: Contract

Job Description

Position Title: Senior Data Engineer

Client: Government of Alberta – Technology and Innovation

Project: Digital Regulatory Assurance System (DRAS)

Location: Edmonton, Alberta – 9942 108 ST, Edmonton, AB T5K 2J5

Work Schedule: 36.25 hours/week (7.25 hours/day, Monday–Friday, 8:15 AM–4:30 PM Alberta Time)

Work Mode: Primarily remote with onsite meetings in Edmonton approximately 3–4 times per fiscal month.

Contract Extension: Up to 6 months.

The Senior Data Engineer will primarily support the 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 Requirements:

  • 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

Other Information

Location Requirement: Must work from within Canada.

Key Responsibilities include designing scalable, secure Microsoft Azure data architectures, building data ingestion and transformation pipelines using Azure Data Factory, Azure Databricks, and Azure Synapse, managing Azure Data Lake Storage Gen2, integrating data from various systems, developing data models, and implementing data governance.


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