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Data Engineer Data Analyst Jobs in Alberta (NOW HIRING)

We are looking for an experienced Senior Data Engineer for our client. This is a permanent position that is completely remote! Our client is a global enterprise company with a product that you've ...

We are looking for an experienced Senior Data Engineer for our client. This is a permanent position that is completely remote! Our client is a global enterprise company with a product that you've ...

We are looking for an experienced Senior Data Engineer for our client. This is a permanent position that is completely remote! Our client is a global enterprise company with a product that you've ...

We are looking for an experienced Junior Data Engineer for our client. This is a permanent position that is remote to start with later relocation to Calgary or Winnipeg . Our client is a global ...

Junior Data Engineer

Edmonton, AB · On-site

  • Medical

  • Dental

  • PTO

We are looking for an experienced Junior Data Engineer for our client. This is a permanent position that is remote to start with later relocation to Calgary or Winnipeg . Our client is a global ...

We are looking for an experienced Senior Data Engineer for our client. This is a permanent position that is completely remote! Our client is a global enterprise company with a product that you've ...

We are looking for an experienced Junior Data Engineer for our client. This is a permanent position that is remote to start with later relocation to Calgary or Winnipeg . Our client is a global ...

We are looking for an experienced Junior Data Engineer for our client. This is a permanent position that is remote to start with later relocation to Calgary or Winnipeg . Our client is a global ...

Bachelors or Diploma in Computer Science, Database Management, Data Programming, Information Systems, Data Engineering, Data Analytics, or other IT-related degree; * Strong database proficiency (e.g ...

Bachelors or Diploma in Computer Science, Database Management, Data Programming, Information Systems, Data Engineering, Data Analytics, or other IT-related degree; * Strong database proficiency (e.g ...

... working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong analytical skills working with unstructured data sets * Knowledge of relational ...

... working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong analytical skills working with unstructured data sets * Knowledge of relational ...

... working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong analytical skills working with unstructured data sets * Knowledge of relational ...

... working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong analytical skills working with unstructured data sets * Knowledge of relational ...

Bachelor's Degree (Computer Science, Technology, Engineering, or related field) * 10+ years of experience as a data analytics developer or engineer * 5+ years of experience in developing data ...

We are looking for an experienced Senior Data Engineer for our client. This is a permanent position that is remote to start with later relocation to Calgary or Winnipeg . Our client is a global ...

We are looking for an experienced Senior Data Engineer for our client. This is a permanent position that is remote to start with later relocation to Calgary or Winnipeg . Our client is a global ...

Senior Manager - Data Engineering

Calgary, AB · On-site +1

CA$120K - CA$160K/yr

Lead the build-out of Canada's Gold/semantic consumption layer with data contracts and SLAs, and retire the legacy analytics warehouse. * Partner with the Lead Data Engineer on system design of our ...

Showing results 21-40

Data Engineer Data Analyst information

How do data engineer data analysts typically collaborate with data scientists and business stakeholders?

Data Engineer Data Analysts play a crucial role in bridging the technical and analytical needs of an organization. They work closely with data scientists by preparing, cleaning, and structuring large datasets to enable advanced analytics and modeling. Additionally, they collaborate with business stakeholders to understand data requirements, translate business questions into technical solutions, and deliver actionable insights. Effective communication and teamwork are essential, as the role often involves facilitating data access, ensuring data quality, and aligning data projects with business objectives.

What are the key skills and qualifications needed to thrive as a data engineer data analyst, and why are they important?

To thrive as a Data Engineer/Data Analyst, you need strong analytical and statistical skills, proficiency in programming languages like Python or SQL, and typically a degree in computer science, statistics, or a related field. Familiarity with data warehousing tools, ETL processes, and experience with platforms like Hadoop, Spark, or Tableau is often required. Attention to detail, problem-solving ability, and effective communication are crucial soft skills for interpreting data and sharing insights with stakeholders. These competencies ensure accurate data management, insightful analysis, and support data-driven decision-making within organizations.

What is the difference between Data Engineer Data Analyst vs Data Scientist?

AspectData EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; often certifications in cloud or data toolsBachelor's or higher in CS, Statistics, or related; often advanced degrees
Work EnvironmentBuilds data pipelines, manages databases, ensures data flowAnalyzes data, creates models, interprets insights
Employer & Industry UsageTech companies, finance, healthcare, e-commerceResearch firms, tech, finance, marketing

Data Engineers focus on developing and maintaining data infrastructure, while Data Scientists analyze data to generate insights. Both roles require strong technical skills, but Data Engineers are more involved in data architecture, whereas Data Scientists focus on modeling and analysis.

What are popular job titles related to Data Engineer Data Analyst jobs in Alberta? For Data Engineer Data Analyst jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Data Engineer Data Analyst jobs in Alberta look for? The top searched job categories for Data Engineer Data Analyst jobs in Alberta are:
What cities in Alberta are hiring for Data Engineer Data Analyst jobs? Cities in Alberta with the most Data Engineer Data Analyst job openings:
Infographic showing various Data Engineer Data Analyst job openings in Alberta as of August 2026, with employment types broken down into 94% Full Time, and 6% Contract. Highlights an 62% In-person, 19% Hybrid, and 19% Remote job distribution.

Director, Data, AI, & Automation Services

Bird Construction

Calgary, AB

Full-time

Posted 7 days ago


Job description

Director, Data, AI, & Automation ServicesAs a member of the Business Systems leadership team reporting to the Vice President, Business Systems, the Director, Data, AI & Automation Services leads Bird's enterprise data, analytics, AI, automation, and information governance services. The role is accountable for translating business strategy into a practical Data, AI & Automation roadmap that improves decision-making, project and operational performance, productivity, and responsible innovation across Bird.
The Director leads the modernization of Bird's data platform and analytics ecosystem, establishes scalable AI and automation capabilities, and advances enterprise data governance, data quality, stewardship, and data fluency. Working with executive sponsors, business leaders, Cybersecurity, Privacy, Enterprise Architecture, and delivery teams, this role ensures data and AI capabilities are trusted, secure, adopted, and measurable in business value.What You Will Be Working On
  • Develop and execute Bird's enterprise Data, AI, Analytics, and Automation strategy, aligned with corporate objectives and the priorities of the Business Systems leadership team, translating business strategy into measurable outcomes across decision-making, operational excellence, and innovation.

  • Establish and maintain a multi-year roadmap and prioritized portfolio for data modernization, AI adoption, analytics, automation services, and information governance - sequencing initiatives by business value, risk, feasibility, and adoption readiness, and reporting quantified value realization to executive leadership.

  • Lead the modernization and operation of Bird's enterprise data platform, including lakehouse, Azure Databricks, semantic models, enterprise data models, metadata, data pipelines, and analytics architecture, in partnership with Business Subject Matter Experts, Data Architects, and Business Analysts.

  • Establish and maintain enterprise standards for analytics, reporting, data engineering, AI solution development, and delivery governance - covering architecture reviews, solution design reviews, testing, release management, training, documentation, and operational support.

  • Lead enterprise data governance, master data management, data quality, metadata, stewardship, and information lifecycle management, ensuring compliance with privacy, cybersecurity, regulatory, and corporate governance requirements - including ownership of the Semarchy MDM tool and enterprise data standards.

  • Establish and operationalize responsible AI governance and lifecycle controls for Generative AI, Microsoft Copilot, machine learning, predictive analytics, and intelligent automation - covering AI inventory, human oversight, third-party AI/data risk, monitoring, incident response, and decommissioning, aligned with recognized frameworks such as NIST AI RMF (Govern, Map, Measure, Manage) and ISO/IEC 42001)

  • Deliver trusted analytics, business intelligence, KPI frameworks, dashboards, predictive models, and AI-enabled solutions - including Power BI visualization on the enterprise Lakehouse - that improve executive, operational, project, and functional decision-making, and leverage structured, unstructured, and IoT data to solve complex business challenges and improve project outcomes.

  • Lead enterprise automation services and the Automation Center of Excellence, including workflow automation, RPA, AI Agents, reusable patterns and templates, citizen-development guardrails, and consistent benefits realization through KPIs, ROI tracking, and process rationalization.

  • Champion enterprise data literacy, AI fluency, self-service analytics, adoption, and change management - including Bird's Data & AI Community of Practice and the Data & AI Fluency Journey - measuring and communicating the business value delivered through data, AI, and automation initiatives.

  • Build, coach, and lead a high-performing Data, AI & Automation Services team across Data Engineers, Data Analysts, Data Scientists, AI Specialists, and Automation professionals, and foster a culture of innovation, continuous improvement, collaboration, and customer service excellence in partnership with executive leadership, Cybersecurity, Enterprise Architecture, Privacy, and business stakeholders.

What We Are Looking For

Education

  • Post-secondary degree in Computer Science, Engineering, Data Science, Information Technology, Business, or a related discipline.

  • Master's degree considered an asset.

Experience

  • Minimum 10 years of progressive experience in Data, Analytics, Artificial Intelligence, Automation, or Digital Transformation. Prior Director-level (or equivalent senior enterprise leadership) experience is required.

  • Demonstrated experience operating at the enterprise leadership level, including partnering directly with executive leadership and cross-functional , influencing strategic decisions, and communicating complex technical concepts in clear business language

  • Minimum 8 years of leadership experience managing high-performing technical teams.

  • Proven experience developing and executing enterprise data and AI strategies.

  • Demonstrated ability to lead organizational change, technology adoption, and enterprise capability-building initiatives , including data literacy, AI fluency, self-service analytics, and responsible AI adoption, across business functions

Technical Knowledge

  • Strong understanding of Artificial Intelligence, Machine Learning, Generative AI, predictive analytics, and business intelligence.

  • Deep knowledge of data warehousing, lakehouse architectures, data governance, and enterprise analytics.

  • Experience with data quality management, master data management, metadata management, and information governance.

  • Knowledge of AI lifecycle management, responsible AI practices, and modern data engineering methodologies.

  • Experience building scalable data platforms and self-service analytics capabilities.

Data Governance and Data Fluency Competencies

  • Proven ability to embed governance and data fluency practices into analytics delivery, automation initiatives, AI adoption, and business transformation programs.

  • Experience translating complex data concepts into clear business language for executives, operational leaders, and cross-functional stakeholders.

  • Ability to promote data fluency across business functions by improving data literacy, self-service analytics adoption, and responsible use of AI-enabled insights.

  • Strong understanding of data quality, metadata management, master data management, privacy, security, and information lifecycle management.

  • Demonstrated ability to establish data governance frameworks, stewardship models, data ownership practices, and enterprise data standards.

Leadership Skills

  • Strategic thinking and business acumen.

  • Strong stakeholder management and executive communication skills.

  • Proven ability to lead organizational change and technology adoption.

  • Excellent verbal, written, and presentation skills.

  • Ability to communicate complex technical concepts to technical and non-technical audiences.

  • Strong problem-solving, decision-making, and organizational skills.

Preferred Qualifications

  • Experience leading enterprise AI adoption initiatives.

  • Experience implementing AI governance and data governance frameworks.

  • Experience in construction, engineering, or project-based industries is considered an asset.

  • Knowledge of project delivery methodologies including Agile and Scrum.

SUCCESS MEASURES

  • Adoption and business value realization of AI-enabled solutions.

  • Growth in enterprise data literacy and analytics adoption.

  • Improvements in data quality and governance maturity.

  • Productivity gains through automation and AI.

  • Delivery of strategic data platform and analytics initiatives.

  • Enhanced decision-making through trusted, accessible, and actionable data.

  • Development of a high-performing Data & Automation Services organization.

APPLICATIONS

Applications are accepted online at www.bird.ca.

Please describe your experience with Business Intelligence, Machine Learning, Agile methodology, Data Warehouses, Generative AI, Data Governance, Data Fluency, and modern cloud data platforms in your cover letter and/or resume.

For Those Who Seek to Redefine

The greatest achievements in history are borne from the greatness within people - where human potential meets vision, and passion fuels evolution. Unlocking this potential is the most important thing we do at Bird.

As a leader in Canadian construction for over 100 years, the impact of our team is etched deeply within the core of our legacy. Beyond Bird, this impact is felt in the fundamental aspects of our everyday lives. From the critical infrastructure we depend on, to the energy and resources that keep us moving - we are powering our communities and shaping Canada's skylines coast-to-coast-to-coast. Entrenched in the foundation of a culture built more than a century ago is an enduring quest to reimagine what is possible. Our impact is greater than ever, and we are looking for those who seek to redefine their story.

What We Believe InWe Put Safety First

A healthy and safe work environment is non-negotiable. We build a culture of operational and psychological safety through engagement, learning and leadership.

We Lead With Honesty

We speak and act with integrity, clarity and care so people can trust our word and our work. Being honest means we can deliver the best outcomes and consistent results.

We Are Stronger Together

Success is a team effort. Our inclusive workplace enables our combined expertise, humility and creativity to unlock our greater potential.

We Are Driven To Do Great Work

We built our name on quality. We have a passion for excellence in our work and relationships that honours our businesses and our industry.

We Create Opportunity

Rooted in a solid foundation, we adapt and grow to face the future. We are committed to elevating each other to chart the best path forward in an evolving world.

At Bird, we value Diversity, Equity, and Inclusion (DE&I) and believe it is essential to our success. We will continue to listen, learn, and take action in our commitment to building progress in our organization, and the industry as a whole. Cultivating an environment where all employees feel included, seen, and have a sense of belonging is core to Bird's culture. We commit to proactively employing a workforce that reflects the communities in which we work, fostering an environment of continuous learning, and never compromising on our values.