Cloud Resourcing
We are seeking talented and versatile Data Engineer(s) to join our dynamic team. The ideal candidate(s) will have a strong foundation in data engineering practices, combined with the analytical skills necessary to derive actionable insights from data. This role involves designing, implementing, and maintaining robust data pipelines and architectures, as well as performing detailed data analysis to support business decisions.
Scope of Services
The Data Engineer(s) will be required on a full-time basis, working across two (2) to three (3) projects. Time, location and frequency of work will vary depending on the needs of the particular project. At the end of each term, it is expected that the Data Engineer(s) may work a maximum of 1,960 hours, unless otherwise agreed upon with the Province. However, Data Engineer(s) may be required to work fewer or more hours depending on the nature and needs of their work.
Services and project deliverables should evolve as the work progresses, in response to emerging user and business needs, as well as design and technical opportunities. However, the following must be delivered (iteratively) over the course of the project:
Data Engineering:
Design, build, and maintain data pipelines on-premises and in the cloud (Azure, GCP, AWS) to ingest, transform, and store large datasets. Ensure pipelines are reliable and support multiple business use cases.
Create and optimize dimensional models (star/snowflake) to improve query performance and reporting. Ensure models are consistent, scalable, and easy for analysts to use.
Integrate data from SQL, NoSQL, APIs, and files while maintaining accuracy and completeness. Apply validation checks and monitoring to ensure high-quality data.
Improve ETL/ELT processes for efficiency and scalability. Redesign workflows to remove bottlenecks and handle large, disconnected datasets.
Build and maintain end-to-end ETL/ELT pipelines with SSIS and Azure Data Factory. Implement error handling, logging, and scheduling for dependable operations.
Automate deployment, testing, and monitoring of ETL workflows through CI/CD pipelines. Integrate releases into regular deployment cycles for faster, safer updates.
Manage data lakes and warehouses with proper governance. Apply security best practices, including access controls and encryption.
Partner with engineers, analysts, and stakeholders to translate requirements into solutions. Prepare curated data marts and fact/dimension tables to support self-service analytics.
Data Analytics:
Analyze datasets to identify trends, patterns, and anomalies. Use statistical methods, DAX, Python, and R to generate insights that inform business strategies.
Develop interactive dashboards and reports in Power BI using DAX for calculated columns and measures. Track key performance metrics, share service dashboards, and present results effectively.
Build predictive or descriptive models using statistical, Python, or R-based machine learning methods. Design and integrate data models to improve service delivery.
Present findings to non-technical audiences in clear, actionable terms. Translate complex data into business-focused insights and recommendations.
Deliver analytics solutions iteratively in an Agile environment. Mentor teams to enhance analytics fluency and support self-service capabilities.
Provide data-driven evidence to guide corporate priorities. Ensure strategies and initiatives are backed by strong analysis, visualizations, and models.
Other Mandatory Requirements
Two (2) project examples must be provided for each proposed resource, which exemplify
and demonstrate the proposed resource s expertise in the selected service area (Data
Engineering). Project examples need to be added to the bottom of the resume. Questions 1
through 5 must be answered for each project example. The Evaluation Team must be able
to determine which project any given answer relates to. Where the answer to a Question is
the same for both projects, this must be clearly stated.
proposed resource s team was engaged in that demonstrates expertise in the
selected service area and role. The overview should clearly describe the data
problem being addressed and the proposed resource s responsibilities from a Data
Engineering perspective.
including any data sensitivity, regulatory, or privacy considerations relevant to the
work.
$500,000, less than $1,000,000 or greater than $1,000,000).
of the project/assignment, including any special considerations with respect to
methodology or processes. In the context of Data Engineering, include how data
pipelines, data quality, performance, reliability, and operational considerations were
addressed. In providing a response, consider quality assurance and communication
across the cross functional team.
project/assignment, particularly those related to Data Engineering. Clearly identify
the tools and technologies the proposed resource personally worked with.
Qualification
Description
Expected
Must Have
Education
Yes/No - Bachelor degree in Computer Science, IT or related field of study.
Bachelor degree in Computer Science, IT or related field of study.
Yes
Work Experience
Duration - Ensuring data quality, security, and governance.
Ensuring data quality, security, and governance.
3 years
Duration - Experience as a Data Engineer and/or Data Analyst.
Experience as a Data Engineer and/or Data Analyst.
5 years
Duration - Experience designing efficient dimensional models (star and snowflake schemas) for...
Experience designing efficient dimensional models (star and snowflake schemas) for warehousing and analytics.
3 years
Duration - Experience developing and maintaining reports, dashboards, and visualizations using...
Experience developing and maintaining reports, dashboards, and visualizations using Power BI, DAX, Tableau, or Python libraries.
3 years
Duration - Experience manipulating and extracting data from diverse on-premises and cloud-based...
Experience manipulating and extracting data from diverse on-premises and cloud-based sources.
5 years
Duration - Experience performing migrations across on-premises, cloud, and cross-database...
Experience performing migrations across on-premises, cloud, and cross-database environments.
3 years
Duration - Experience using Git, collaborative workflows, CI/CD pipelines, containerization...
Experience using Git, collaborative workflows, CI/CD pipelines, containerization (Docker/Kubernetes), and Infrastructure as Code (Terraform, ARM, CloudFormation) to deploy and migrate data solutions.
2 years
Duration - Experience with SSIS, Azure Data Factory (ADF), and using APIs for extracting and...
Experience with SSIS, Azure Data Factory (ADF), and using APIs for extracting and integrating data across multiple platforms and applications.
3 years
Nice to Have
Work Experience
Duration - Experience in application development, with knowledge of object-oriented and functional..
Experience in application development, with knowledge of object-oriented and functional programming/scripting languages.
2 years
Duration - Experience in the Government of Alberta environment or an environment of...
Experience in the Government of Alberta environment or an environment of equivalent size and complexity.
1 years
Duration - Experience with databases and data integration, including PostgreSQL, MongoDB, Azure...
Experience with databases and data integration, including PostgreSQL, MongoDB, Azure Cosmos DB and data intefration tools like Synapse pipeline, Fabric data factory, Informatica, Talend, DBT and Airbyte.
2 years
Duration - Exposure to AI/ML tools and workflows relevant to...
Exposure to AI/ML tools and workflows relevant to data engineering, such as integrating AI-driven analytics or automation within cloud platforms like Databricks and Azure.
1 years