Senior Data Analyst

Bird Construction•Edmonton, AB

14d•Hybrid

About The Position

Reporting to the Manager, Business Intelligence & Analytics, the Senior Data Analyst will have a deep understanding of Data, AI, and Analytics solutions. You will be responsible for designing, developing, and delivering effective storytelling solutions using Power BI and Bird’s modern analytics platform. We are seeking an individual who is proactive, curious, and driven—someone who understands not just how to build dashboards, but how to enable a culture of data analytics. This role is ideal for an individual with a strong sense of the big picture: how data governance, storytelling, tools, and people come together to enable better decisions. You will play a key role in advancing Bird’s analytics maturity by delivering trusted insights, promoting effective data storytelling, and contributing to the Data & AI Center of Excellence (CoE) through standards, enablement, and data fluency. The ideal candidate is comfortable navigating complexity, managing multiple priorities, and working across both Agile and Waterfall delivery models—partnering effectively with business, engineering, and leadership teams. This position follows a hybrid work model with regular in office presence. Bird Construction, a leader in Canadian construction for over 100 years, is committed to diversity, equity, and inclusion, fostering an environment where all employees feel included, seen, and have a sense of belonging. They aim to proactively employ a workforce that reflects the communities in which they work, fostering continuous learning and upholding their values.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Business Analytics, or a related field.
5+ years of experience in a Senior Data Analyst or Business Intelligence role.
Strong hands‑on experience with Power BI, with an emphasis on insight, clarity, and usability rather than just visual complexity.
A proactive, self‑driven mindset — comfortable taking ownership, identifying gaps, and helping move analytics forward.
Demonstrated understanding of what building a data‑driven culture actually means, beyond tools alone.
Experience contributing to or working within a Center of Excellence–style model for Data, AI, Analytics, or BI.
Solid grasp of data governance fundamentals, including trusted metrics, standard definitions, and consistency of logic.
Strong communication and organizational skills, with the ability to work effectively across both technical and non‑technical audiences.
Experience working in both Agile and Waterfall delivery environments.
Ability to manage competing priorities with structure, judgment, and professionalism.
General understanding of the Microsoft Power Platform (Power Apps / Power Automate) without requiring deep specialization.

Nice To Haves

Experience delivering insights from structured, semi‑structured, and unstructured data sources.
Working knowledge of SQL and structured data querying.
Familiarity with modern data lakehouse architectures and exposure to platforms such as Databricks, Microsoft Fabric, or Synapse Analytics.
Power BI or relevant Microsoft analytics certification.
Experience enabling or mentoring others through data education, documentation, or informal means.

Responsibilities

Design, develop, and deliver high‑quality analytics solutions using Power BI, ensuring accuracy, reliability, and consistency of data and metrics.
Apply effective data storytelling principles to transform complex information into clear, compelling, and decision‑ready insights.
Partner with stakeholders to understand business context, ask the right questions, and translate analytical needs into meaningful dashboards and reports.
Contribute to the evolution of the Data & AI Center of Excellence (CoE), helping shape standards, best practices, templates, and shared ways of working.
Promote data governance concepts by reinforcing trusted metrics, clear definitions, consistent logic, and proper documentation.
Support and advance data fluency and literacy across the organization by helping stakeholders better interpret, question, and use analytics effectively.
Perform analytical investigations and root‑cause analysis to explain trends, variances, and anomalies in business performance.
Collaborate with Data Engineering and IT teams to ensure analytics solutions align with data Lakehouse architecture and enterprise platforms.
Demonstrate a strong understanding of Data Lakehouse concepts, with exposure to tools such as Databricks, Microsoft Fabric, or Microsoft Synapse Analytics, sufficient to collaborate effectively with engineering teams.
Navigate and contribute within both Agile and Waterfall project environments, adapting communication and delivery style as needed.
Manage multiple priorities simultaneously while maintaining quality, structure, and stakeholder confidence.
Maintain strong, proactive communication with stakeholders and contribute to successful project outcomes.
Stay current with analytics trends and Microsoft’s analytics ecosystem (Power BI, Lakehouse platforms, and related technologies), applying learnings pragmatically.