Senior Data Engineer

Project Overview

The Government of Alberta (GoA) has embarked on transforming the work of government to deliver simpler, more efficient, and better services for the citizens of Alberta, thereby ensuring that the needs of Albertans are effectively met in the digital age. The Province has a strategic role within government to drive efficiencies, innovation and modernization. The Digital Design and Delivery Division (DDD) is the Province’s new centre for digital delivery. It was established to maximize capability and confidence in modern digital practice by ensuring service quality and value through standards and controls. This includes utilizing human-centred design approaches together with agile methodology and modern data practices.

DDD is currently working with Ministries across the GoA, establishing working relationships with partner Ministries throughout this engagement.

The Province is looking for one (1) Data Engineer to work with DDD on service innovation, program review, and digital transformation projects across the GoA. Data Engineers will work as part of cross-functional program review or product delivery teams. These teams, led by GoA product owners and DDD work collaboratively and collectively participate in a full range of activities including: field research; backlog definition and refinement; and sprint planning and execution. Digital transformation projects review the current state of services, identify future opportunities, and then deliver new services that are efficient, effective and affordable.

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, as directed by the Province.

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.

The Province and the Contractor shall determine changes to Services and Materials as required. The Province and the Contractor will determine changes to Services and Materials through the Artifacts.

Location of Work

Data Engineer(s) will primarily work remotely; however, may be required to attend meetings or work sessions in Edmonton on reasonable notice from the Province. At the time of providing such notice, the Province will advise of the expected duration of any such meetings or work sessions. However, time to travel and any associated expenses to and from Edmonton will be at no cost to the Province.

The Province reserves the right to alter this work arrangement on reasonable notice to the Data Engineer(s). The Supplier and the Data Engineer(s) will be consulted about the alteration in work arrangement; however, the Province retains ultimate discretion as to the appropriate work arrangement.

Some travel within Alberta may be required to conduct field research and user interviews. The Province will make arrangements for travel for field research and user interview purposes where possible at no cost to the province.

Work must be done within Canada.

Facilities

Data Engineer(s) shall be responsible for providing all of their equipment, including computers, software, printers, supplies, desks and chairs. However, the Province shall ensure that the Data Engineer(s) have the necessary access and credentials to the GoA system.

In the event that the Data Engineer(s) are directed to work in-person, the Province shall provide the requisite office space, furniture and office supplies. However, the Data Engineer(s) shall continue to be responsible for providing computers and software and the Province shall continue to ensure that the Data Engineer(s) have the necessary access and credentials to the GoA system.

The virtual meeting tool for the Province is Microsoft Teams. Zoom may sometimes be used when needed, however, Zoom accounts are not provided by the Province.

Criminal Records Checks

Upon request by the Province, the Data Engineer(s) shall, at no cost to the Province, provide a current criminal record check. A Data Engineer may be rejected if, in the opinion of the Province, the criminal record is unacceptable.

Should a Data Engineer be assigned to a team working for Justice, the Data Engineer must, prior to performing Services, provide the Province with an “Enhanced Security Clearance”. The supplier will be responsible for providing the GoA with a credit check for the awarded candidate. Data Engineer, which in the opinion of the Province have an unacceptable “Enhanced Security Clearance” or equivalent, shall be rejected. The Province does not receive any information specific to the reason an enhanced clearance may be rejected. Participating law enforcement agencies only identify if an applicant’s clearance is not accepted.

Data Engineer should be aware that over the course of the WO, Data Engineer may be required to complete higher-level security clearances, such as the “Royal Canadian Mounted Police Top Secret Clearance.” Please ensure applicants are eligible to apply if required by the ministry.

Acceptance by the Province of all Data Engineer requires written approval from the Province following acceptable security clearances.

Evaluation

The evaluation criteria will be distributed within the following categories. Subject to the requirements of Protection of Privacy Act (POPA) and Access to Information Act (ATIA), the evaluation of Responses shall be confidential, and not released to any party.

• Qualifications- 20%
• Other Mandatory Requirements- 20%
• Interview - 50%
• Pricing - 10%

Other Mandatory Requirements - See attached PDF File at the bottom of this job posting for reference.

Incumbency

1 Net new position

Mandatory Training Courses

• Once hired the resource will be required to complete all mandatory training which includes but not limited to Protection of Privacy Act (POPA) and Access to Information Act (ATIA), Security/Cybersecurity, Information Management, and Respect in the Workplace. There may also be other mandatory and/or optional training.

Anticipated Interviews dates

• Two weeks after the posting halts. Subject to change.

Must Have Education

• Bachelor degree in Computer Science, IT or related field of study.

Must Have Work Experience

• 3 years - Ensuring data quality, security, and governance.
• 5 years - Experience as a Data Engineer and/or Data Analyst.
• 3 years - Experience designing efficient dimensional models (star and snowflake schemas)
• 3 years - Experience developing and maintaining reports, dashboards, and visualizations
• 5 years Experiencece manipulating and extracting data from diverse on-premises and cloud-based
• 3 years - Experience performing migrations across on-premises, cloud, and cross-database.
• 2 years - Experience using Git, collaborative workflows, CI/CD pipelines, containerization...
• 2 years experience with SSIS, Azure Data Factory (ADF), and using APIs for extracting

Contract Details

• Maximum Extension Term (Months): 24
• Job Type: Fixed term contract
• Contract length: 12 months
• Pay: $100.00 per hour
• Expected hours: 36.25 per week

Benefits

• Casual dress
• Flexible schedule
• Work from home