Data Engineer - Senior

Job ID:GOAPRDJP00000982

Rate:70 to 100 per hour

Term : 12 Months + optional 24-months extension

Location: Work must be done within Canada (Primarily remote; occasional on‑site meetings in Edmonton with reasonable notice).

Engagement Type: Contract (B2B)

Position Overview

We are seeking an experienced Data Engineer for a contract opportunity supporting the Government of Alberta (GoA).

The Government of Alberta is transforming how government services are designed and delivered to provide simpler, more efficient, and better services for Albertans. The Digital Design and Delivery (DDD) division supports this transformation by partnering with ministries to design and deliver modern digital products, platforms, data solutions, and services.

Working within multidisciplinary product teams, the Data Engineer will collaborate with business and technical stakeholders to understand data requirements and design, build, and enhance modern data solutions.

The successful candidate will bring strong data engineering expertise combined with analytical capabilities, supporting the development of scalable data pipelines, integrations, data models, analytics solutions, reporting, and data governance practices.

This role will contribute to improving data quality, accessibility, analytics capabilities, and evidence-based decision-making across Government of Alberta ministries.

Scope of Services:

Services and project deliverables should evolve as the work progresses in response to emerging user and business needs, as well as evolving design and technical opportunities. However, the following deliverables must be delivered iteratively throughout the course of the project:

Data Engineering:

- Design, build, and maintain scalable data pipelines across on-premises and cloud platforms (Azure, Databricks, Microsoft Fabric, GCP, AWS) to ingest, transform, and store diverse datasets in support of enterprise business use cases.
- Develop, optimize, and maintain data models, including dimensional models (star and snowflake schemas), to improve query performance, scalability, and usability for analytics and reporting.
- Integrate data from a variety of sources, including relational databases, NoSQL platforms, APIs, and files, applying AI-enabled data integration techniques such as intelligent data mapping, schema discovery, metadata enrichment, and automated data quality validation to improve accuracy and efficiency.
- Enhance ETL/ELT processes through optimization, automation, and performance tuning to improve scalability, reduce bottlenecks, and support high-volume data processing.
- Develop and operate end-to-end ETL/ELT workflows using tools such as SSIS, Azure/Fabric Data Factory, Dataflows, and Notebooks, incorporating data validation, error handling, logging, monitoring,



and scheduling to ensure reliable data operations.
- Automate data pipeline deployment and operations through CI/CD practices, including automated testing, release management, and monitoring to enable faster and more reliable delivery.
- Support the management and governance of enterprise data platforms, including data lakes, data warehouses, security controls, and access management.
- Partner with architects, developers, and stakeholders to translate requirements into solutions, and prepare curated data marts and fact/dimension tables to support 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 Power BI dashboards and reports, leveraging DAX to create calculated columns and measures, monitor key performance indicators, deliver service dashboards, and communicate results effectively to stakeholders.
- 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 setting. Mentor teams to enhance analytics fluency and support self-service capabilities.
- Provide data-driven analysis, visualizations, and AI-enabled insights to support corporate priorities, strategic initiatives, and informed decision-making.
- 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.

Must Have

- Bachelor degree in Computer Science, Information Technology, Engineering, Mathematics, Statistics, Data Science, or a related field.
- Business Intelligence and Executive Reporting: Built executive dashboards, KPI reporting, self-service BI solutions and business performance reporting.
- Cloud or Hybrid Data Platforms: Experience with Cloud modernization, or hybrid/cloud data platform implementations.
- Data Migration and Modernization: Plan, execute, validate, and support data migrations across on-premises, cloud, and cross-database environments.
- Data Warehouse and Lakehouse Design:



Enterprise data warehouse or lakehouse projects using Star/Snowflake schemas, fact/dimension modeling.
- Experience as a Data Engineer and/or Data Analyst.
- Experience in Python (including PySpark) and SQL, applied to developing, orchestrating, and optimizing enterprise-grade ETL/ELT workflows in a large-scale cloud environment.
- Knowledge of ETL processes and tools, with hands-on experience designing and implementing data pipelines for transforming and loading data from multiple sources into data warehouses.

Nice to Have

- Experience in AI-Assisted Development Tools and Practices: Leverage AI-assisted development tools to improve productivity, code quality, documentation, testing, and data engineering workflows while applying appropriate review and quality controls.
- Experience in DevOps, CI/CD, and Infrastructure as Code: Designing, implementing, or maintaining CI/CD pipelines and Infrastructure as Code practices to support automated deployment, configuration, and management of cloud-based data platforms and services.
- Modern data technology: Experience in modern data technologies such as Microsoft Fabric, Databricks, Spark, Delta Lake, or similar lakehouse and big data platforms.
- The proposed resource must have experience supporting enterprise-scale for public service applications in public sector, or mixed delivery environments.

Why Join

- Work on meaningful public-facing services used by thousands of Albertans.
- Highly cooperative, modern digital environment.
- Opportunity to influence large-scale service improvements across government.

How to Apply

- Apply directly through Indeed or send your resume to: [email protected]
- Please include three professional references where similar work was performed.
- List your most recent reference first.

Interested in more opportunities with us?

Visit our careers page: www.shabech.ca to browse current openings.

About Shabech Consulting

Shabech Consulting specializes in Business and IT consulting, strategic staffing, and project management services. Our mission is to help organizations achieve efficiency, innovation, and measurable results by connecting them with exceptional talent and tailored solutions. We take a collaborative approach to understanding each client’s unique challenges and delivering strategies that create real impact. Whether supporting complex digital projects, providing specialized resources, or optimizing operations, we are committed to excellence.

As a trusted partner across multiple industries, Shabech Consulting helps organizations turn strategy into action and achieve their goals with confidence.

We thank all applicants for their interest. Only candidates selected for the next stage will be contacted

Pay: $70.00-$100.00 per hour

Work Location: Remote

📌 Data Engineer - Senior (Canada)
🏢 Shabech IT Services
📍 Canada