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Manager Data Analytics Engineer Jobs in Ottawa, ON

Data Analytics Specialist

Ottawa, ON · On-site

  • Medical

  • Dental

  • Life

  • Retirement

Data Analytics Specialist Take a central role The Bank of Canada has a vision to be a leading ... At the Bank, data is at the core of how we make decisions, manage performance, and continuously ...

BI Developer, Data & Analytics

Ottawa, ON · Remote

  • Medical

  • Dental

  • Retirement

  • PTO

Job Title BI Developer, Data & Analytics About This Role: Workplace Arrangements : This is a fully ... Follow SDLC, Change Management, deployment, documentation, and DevOps procedures as defined by the ...

... engineers. * Investigate root causes of data quality problems and provide evidence-based ... Bachelor's degree in Data Analytics, Computer Science, or a related field. * 5+ years of experience ...

Data Scientist

Ottawa, ON · On-site

  • Medical

  • Dental

  • PTO

Perform data analysis, visualization, and modelling with large datasets; * Independently ... Strong object-oriented programming in Python; * Strong communication skills; * Ability to work in a ...

Data Engineer

Ottawa, ON · Hybrid

  • Medical

  • Dental

  • Life

  • Retirement

  • PTO

More specifically, you will work with business analysts and operational stakeholders to identify ... Support data initiatives such as Technical Data Package management, data migration and Condition ...

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Showing results 1-20

Manager Data Analytics Engineer information

What is the difference between Manager Data Analytics Engineer vs Data Analytics Engineer?

AspectManager Data Analytics EngineerData Analytics Engineer
Required CredentialsBachelor's or Master's in Data Science, Analytics, or related field; often leadership experienceBachelor's or Master's in Data Science, Analytics, or related field
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersDevelops data models, analyzes data, implements solutions
Employer & Industry UsageUsed in tech, finance, healthcare, and large enterprisesCommon in similar industries, often within data teams

The main difference is that a Manager Data Analytics Engineer oversees teams and projects, focusing on leadership and strategic planning, while a Data Analytics Engineer primarily develops and implements data solutions. Both roles require strong technical skills, but the manager role adds a layer of team management and stakeholder communication.

How does a manager data analytics engineer typically balance technical project work with team leadership responsibilities?

As a Manager Data Analytics Engineer, you are expected to split your time between overseeing complex analytics engineering tasks and guiding your team’s development. This involves setting project priorities, conducting code reviews, and ensuring data solutions align with business goals, while also mentoring team members and facilitating collaboration with stakeholders like data scientists and business analysts. Successful managers often establish clear communication channels and delegate tasks effectively, so they can stay hands-on with key projects while supporting the professional growth of their team.

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

To thrive as a Manager Data Analytics Engineer, you need a strong background in data engineering, analytics, and leadership, typically with a degree in computer science or a related field. Familiarity with tools like SQL, Python, data warehousing platforms (e.g., Snowflake, Redshift), and certifications in cloud technologies or data management are common requirements. Excellent communication, problem-solving, and team management skills set top performers apart in this role. These competencies are essential for driving data strategy, ensuring data quality, and leading analytics teams to deliver actionable business insights.

What is a manager data analytics engineer?

A Manager Data Analytics Engineer is a professional who leads a team of data analytics engineers responsible for designing, building, and maintaining data systems and analytics solutions. They oversee data pipeline development, ensure data quality, and collaborate with stakeholders to translate business requirements into technical solutions. In addition to technical expertise, they manage project timelines, mentor team members, and help drive data-driven decision-making across the organization.

What are popular job titles related to Manager Data Analytics Engineer jobs in Ottawa, ON?

For Manager Data Analytics Engineer jobs in Ottawa, ON, the most frequently searched job titles are:

What job categories do people searching Manager Data Analytics Engineer jobs in Ottawa, ON look for?

The top searched job categories for Manager Data Analytics Engineer jobs in Ottawa, ON are:

What cities near Ottawa, ON are hiring for Manager Data Analytics Engineer jobs?

Cities near Ottawa, ON with the most Manager Data Analytics Engineer job openings:

Data Analytics Engineer - Corporate Data Analytics Group

Canadian Bank Note Company

Nepean, ON • On-site, Remote

Full-time

Medical, Life, Retirement

Re-posted 22 days ago


Job description

Company Description

Canadian Bank Note Company (CBN) is a leader and trusted provider of secure document and adjacent enterprise-level system solutions across the following domains: border security, civil identity, driver licence/identification and vehicle information, excise control, currency, lotteries and charitable gaming.

Our Corporate Philosophy and 7 Core Principles shape and guide our corporate behaviours and underpin the sense of community you will experience at CBN. We seek long-term relationships with our employees and offer a competitive compensation package that includes health, medical and life insurance benefits and a defined contribution pension plan with company matching.

Job Description

Internal Job Title: Data Analytics Engineer

Job Type: Permanent, Full-time

Location: Ottawa, Ontario

Work Model: Remote

Job Status: Existing Vacancy

Position Summary

The Data Analytics Engineer plays a critical role in preparing enterprise data to be AI-ready by designing rich semantic layers and business context that enable advanced analytics, self-service BI, and AI-powered decision-making. This role focuses on transforming curated data into trusted, governed, and reusable data products that can be safely consumed by business users, copilots, and machine learning models across the organization.

Key Responsibilities

Business Partnership & Domain Alignment

  • Partner with business stakeholders to translate domain knowledge into structured analytical and semantic representations.

Semantic Modeling & Data Foundation

  • Design, develop, and maintain enterprise semantic models that represent business meaning, metrics, and relationships across data domains.
  • Collaborate with data engineers to shape silver and gold datasets that support semantic clarity and downstream AI consumption.
  • Build AI-ready data products by enriching datasets with business definitions, hierarchies, metadata, and contextual logic.

BI Development & Metric Standardization

  • Develop and optimize Power BI semantic models, datasets, and metric layers to support BI, Copilot, and AI use cases.
  • Create and manage standardized KPIs and calculations using DAX, ensuring consistency and reuse across analytics and AI workloads.
  • Document business logic, data definitions, and metric context to support discoverability and AI-assisted querying.

Governance, Security & Trusted Data

  • Implement data governance controls including row-level security (RLS), object-level security, sensitivity labels, and certified datasets.

Data Product Enablement & AI Integration

  • Publish trusted semantic models and datasets to enable self-service and AI-assisted analytics at scale.
  • Support integration of analytics models with AI and ML workflows, including retrieval-augmented generation (RAG) scenarios.

Performance Optimization & Reliability

  • Monitor and optimize model performance, refresh reliability, and query efficiency.

Standards & Continuous Improvement

  • Contribute to analytics and AI standards and best practices through the Data & AI Community of Practice.
Qualifications

Mandatory Requirements

  • Legally eligible to work in Canada.
  • Fluent in English (speak, read, write).
  • Able to obtain (in a timely manner) and maintain Government of Canada Secret (Level II) security clearance.

Minimum Qualifications

  • Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, or a related field.
  • Understanding of the following:
    • Semantic modeling concepts including metrics, hierarchies, and dimensional modeling.
    • Data governance principles and secure data access patterns.
  • 8+ years of relevant professional experience, including:
    • 3+ years of professional experience in analytics, business intelligence, or data modeling roles.
    • 3+ years of hands-on experience with Power BI semantic modeling, DAX, and dataset design.
    • 3+ years of experience working with SQL-based analytical datasets.
    • Ability to translate business concepts into structured analytical and semantic representations.

Preferred Qualifications

  • Microsoft Certifications:
    • Power BI Data Analyst Associate (PL-300) or Fabric Analytics Engineer Associate (DP-600).
  • Knowledge of data catalogs, business glossaries, and metadata management.
  • Experience with the following:
    • Microsoft Fabric semantic models, OneLake, and data products.
    • Preparing datasets for AI/ML or Copilot scenarios (e.g., feature tables, RAG inputs).
    • Manufacturing, software, or regulated environments.

Additional Information

Equal Opportunity Statement

Our organization is committed to employment equity and diversity in the workplace. We actively encourage applications from women, Indigenous Peoples, persons with disabilities, members of visible minorities, and LGBTQ2+ individuals.

We are dedicated to removing barriers and fostering an inclusive workplace that reflects society and we are committed to providing an accessible and inclusive recruitment process in accordance with the Accessibility for Ontarians with Disabilities Act (AODA).

If you require accommodation at any stage of the hiring process, please contact us at recruitment@cbnco.com so that appropriate arrangements can be made.

AI Use in Recruitment Statement

As part of our commitment to transparency and fairness in hiring, we disclose that artificial intelligence (AI) tools may be used at certain stages of our recruitment process. These tools assist in tasks such as resume screening, candidate matching, and interview scheduling. All AI-assisted decisions are subject to human oversight to ensure fairness, accuracy, and compliance with applicable laws.

We are committed to the responsible, transparent, and accountable use of AI, in alignment with Ontario’s Responsible Use of Artificial Intelligence Directive and the requirements under the Working for Workers Four Act. This includes taking steps to mitigate bias, protect candidate privacy, and ensure that AI does not unfairly influence hiring outcomes.

If you have questions or concerns about how AI is used in our hiring process, please contact us at recruitment@cbnco.com .