Data Analyst

Client: Public Sector

Role: Data Analyst

Duration: 7 months (option to extend up to 2 years)

Hours: 36.25 hrs/week

Location: Remote (must work MST core hours and be available for occasional onsite work as required; must be based in Canada)

Position Overview

The client requires a Data Analyst to support service innovation, program review, and digital transformation initiatives across multiple public-sector service areas. The Data Analyst will work as part of cross-functional program review or product delivery teams, collaborating closely with product owners, delivery leads, and internal stakeholders.

Teams operate in an Agile delivery environment, participating in activities such as field research, backlog definition and refinement, sprint planning, and execution. Digital transformation projects involve assessing current-state services, identifying future opportunities, and delivering new solutions that are efficient, effective, and cost‑conscious.

We are seeking a versatile Data Analyst with a strong foundation in data engineering practices, paired with deep analytical skills to produce actionable insights. The role includes designing, implementing, and maintaining data pipelines and architectures, alongside advanced data analysis to support strategic decision-making.

Scope of Services

The engagement is anticipated to last seven (7) months, with the option to extend the contract for up to twenty-four (24) additional months under the same terms and conditions.

The Data Analyst will work full time (7.25 hours per day) across multiple initiatives. Work schedules and locations may vary based on project requirements. At the end of each term, total hours may reach up to 1,960 hours, unless otherwise agreed upon. Variations in hours may occur depending on project needs.

Services and deliverables will evolve iteratively in response to emerging user needs, business priorities, and technical opportunities.

Key Deliverables

Data Engineering

• Design, develop, and maintain scalable data pipelines to ingest, transform, and store large volumes of data across on‑premises environments (e.g., SSIS) and cloud platforms (Azure, AWS, GCP)
• Ensure data integrity, accuracy, and availability for analytical and operational use
• Collaborate with software engineers, data scientists, and business stakeholders to gather requirements and implement solutions
• Optimize and improve existing data workflows and ETL/ELT processes
• Implement data governance, security, and compliance best practices
• Manage data storage solutions including data lakes and data warehouses
• Demonstrate success manipulating, processing, and extracting value from large, disconnected datasets
• Deploy data solutions using SQL and NoSQL technologies
• Support cloud‑based data deployments and integrations

Data Analytics

• Perform exploratory data analysis to identify trends, patterns, and insights
• Develop and maintain reports, dashboards, and visualizations using BI tools such as Power BI
• Conduct statistical analysis and modeling to support business and operational strategies
• Communicate insights and recommendations clearly to technical and non‑technical stakeholders
• Use SQL and other query languages to extract and manipulate data from multiple sources
• Develop strategies to integrate data models and improve service delivery
• Create and share service metrics and performance dashboards
• Support frequent delivery of analytics outputs while mentoring Agile teams to improve analytics literacy
• Provide data‑driven evidence to support organizational priorities

Requirements

Education

• Bachelor’s degree in Computer Science, Information Technology, or a related field

Work Experience (Must Have)

• 5+ years of experience as a Data Analyst and/or Data Engineer
• 3+ years designing dimensional data models (star and snowflake schemas)
• 3+ years developing and maintaining reports, dashboards, and visualizations
• 3+ years ensuring data quality, security, and governance
• 5+ years extracting and manipulating data from on‑premises and cloud-based sources
• 2+ years performing data migrations across on‑prem, cloud, and cross‑database environments
• 2+ years using Git, collaborative workflows, CI/CD pipelines, and containerization
• 3+ years working with SSIS, Azure Data Factory (ADF), and APIs for data integration
• 2+ years in advanced analytics (e.g., statistical modeling, predictive analytics)
• 1+ year working in a public-sector or comparable regulated environment
• 2+ years experience with Azure Databricks
• 2+ years using object‑oriented and functional programming or scripting languages
• 1+ year experience working with AI technologies (e.g., machine learning, NLP)

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