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We analyzed 70+ Alberta data job postings across energy, public sector, financial services, technology, and professional services. The goal was to understand the real landscape — not just what job titles exist, but what employers actually need and how accessible those roles are to Albertans from different starting points.
Methodology: Job postings were collected from LinkedIn, Indeed, and employer career pages between January and March 2026. Analysis focused on stated requirements, not inferred ones.
We surveyed 47 working data professionals across Canada, the United States, the UK, and Australia. Respondents included individual contributors and organizational leaders. 74% work in conventional energy — consistent with PPDM's network. The full breakdown spans organizations from 25-person firms to global enterprises with 10,000+ employees.
“The public narrative around AI and jobs is generating anxiety that isn't supported by the experience of people actually doing data work. We have data to push back with.”
On the question of AI's impact on their own roles: 52% expect it to change the type of work they do without reducing headcount. Only 10% feel genuinely at risk of replacement. The picture from people closest to the work is more stable than the headlines suggest.
Methodology: Survey conducted Q1 2026. Respondents sourced through PPDM Association networks and DAMA chapters. n=47. Results should be interpreted as a global energy sector signal, with 74% of respondents working in conventional energy.
We interviewed ten employers across eight industries: healthcare, conventional energy, agriculture, financial services, utilities, professional services, technology, and construction and industrial. Every organization uses structured data in its operations. Seven of ten hold direct hiring authority.
“The public narrative around AI and jobs is generating anxiety that isn't supported by the experience of people actually doing data work. We have data to push back with.”
On the question of AI's impact on their own roles: 52% expect it to change the type of work they do without reducing headcount. Only 10% feel genuinely at risk of replacement. The picture from people closest to the work is more stable than the headlines suggest.
Methodology: Survey conducted Q1 2026. Respondents sourced through PPDM Association networks and DAMA chapters. n=47. Results should be interpreted as a global energy sector signal, with 74% of respondents working in conventional energy.
Data Analyst and Data Architect were the most commonly cited near-term hiring priorities. Entry-level analyst positions are the most realistic landing spot for program graduates. Senior roles are largely stable — organizations are hiring at the bottom of the experience curve, not the top.
Seven of ten weight demonstrated skills and experience at least as highly as formal credentials. In practice, credentials get candidates past initial screening — the hire happens on demonstrated ability. That gap is exactly what this program is built to close.
Competing internal priorities and difficulty reconciling data from external sources were the most common barriers. Seven of ten cited competing priorities. This reinforces the global survey result: the bottleneck is organizational alignment, not skills scarcity.
Methodology: Interviews conducted April-May 2026. Respondents sourced through PPDM Association networks and Phase 1 employer contacts. n=10 across 8 industries. To protect confidentiality, findings are presented by industry only — no individual names or company names are included.