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Manager Data Engineering Jobs in Calgary, AB (NOW HIRING)

Senior Database Developer

Calgary, AB · Remote

$95K - $110K/yr

We are looking for an experienced Data Developer for our client. This is a permanent position ... Your role will encompass managing, building, planning administrating and maintaining infrastructure ...

Senior Database Developer

Calgary, AB · Remote

$95K - $110K/yr

We are looking for an experienced Data Developer for our client. This is a permanent position ... Your role will encompass managing, building, planning administrating and maintaining infrastructure ...

... technologies to manage their business more effectively. Headquartered in Texas, we have 450 ... Master's degree in computer science, software engineering, data science, or a related field (PhD ...

... management * System Integration, Observability, and Data Engineering Fundamentals: Experience with SQL and API integrations * Cloud-Native Software Engineering:Proven experience designing, developing ...

Manager, Machine Learning Engineering

Calgary, AB · Remote

CA$181K - CA$272K/yr

Collaborate cross-functionally with MLOps engineering, product management, operations, and data science to identify new tooling for ML and LLM-driven features for Clio customers. * Work in an agile ...

Data Engineering and Pipelines Build pipelines for ingesting, cleaning, transforming, and preparing spatial datasets for machine learning. Manage training datasets, versioning, and evaluation ...

Research and understand AltaLink's asset data and compliance requirements for Substations, P&C ... Strong organizational, planning and time management skills; * Proactive, results focused approach ...

Showing results 41-60

Manager Data Engineering information

See Calgary, AB salary details

$81.5K

$129.4K

$224.5K

How much do manager data engineering jobs pay per year?

As of Sep 11, 2026, the average yearly pay for manager data engineering in Calgary, AB is $129,416.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are the roles and responsibilities of a manager data engineering?

A Manager Data Engineering oversees teams that design, build, and maintain data infrastructure and pipelines for organizations. They are responsible for ensuring the efficient flow and storage of data, implementing best practices in data management, and collaborating with stakeholders to meet business data needs. Additionally, they mentor and guide data engineers, manage project timelines, and ensure data security and quality standards are met. Their role often involves strategic planning to enable data-driven decision making across the company.

What are the key skills and qualifications needed to thrive as a manager data engineering?

To thrive as a Manager Data Engineering, you need expertise in data architecture, advanced analytics, and leadership, typically supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), data warehousing systems, cloud platforms (AWS, Azure), and certifications such as AWS Certified Data Analytics are highly valued. Strong communication, problem-solving, and team management skills help drive project success and foster collaboration. These skills ensure effective data solutions, alignment with business goals, and the ability to lead and grow high-performing engineering teams.

How does a manager data engineering typically collaborate with data scientists and business stakeholders?

A Manager of Data Engineering often serves as a bridge between technical teams and business stakeholders. They work closely with data scientists to ensure that data pipelines and infrastructure meet analytical needs, while also translating business requirements into actionable engineering solutions. Regular coordination meetings, clear documentation, and cross-functional projects are common, enabling seamless collaboration and alignment on goals. This role requires strong communication skills and the ability to balance technical priorities with business objectives.

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

AspectManager Data EngineeringData Engineer
Required CredentialsBachelor's or Master's in CS, Data Science, or related; often leadership experienceBachelor's or higher in CS, IT, or related; technical certifications optional
Work EnvironmentTeam leadership, project management, strategic planningData pipeline development, coding, data modeling
Employer & Industry UsageTech companies, finance, healthcare, where data teams are commonData-focused roles across various industries

The main difference is that Manager Data Engineering oversees data teams and projects, focusing on strategy and leadership, while Data Engineers handle the technical implementation of data pipelines and infrastructure. Managers typically have more experience and leadership skills, whereas Data Engineers are more hands-on with coding and data architecture.

What are the most commonly searched types of Data Engineering jobs in Calgary, AB?

The most popular types of Data Engineering jobs in Calgary, AB are:

What are popular job titles related to Manager Data Engineering jobs in Calgary, AB?

For Manager Data Engineering jobs in Calgary, AB, the most frequently searched job titles are:

What job categories do people searching Manager Data Engineering jobs in Calgary, AB look for?

The top searched job categories for Manager Data Engineering jobs in Calgary, AB are:

Infographic showing various Manager Data Engineering job openings in Calgary, AB as of August 2026, with employment types broken down into 87% Full Time, 12% Part Time, and 1% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $129,416 per year, or $62.2 per hour.

Senior AI/ML Engineer

Calgary, AB • On-site

Full-time

Posted 2 days ago

New


Job description

Join the dynamic and collaborative team at Katalyst Data Management (KDM)! KDM is seeking a Senior AI/ML Engineer to help design, build, and operate the infrastructure that powers our next generation of AI-enabled data solutions. This is an exciting opportunity for a hands-on technical leader who can scale production AI/ML systems, optimize GPU and cloud environments, and deliver reliable, secure platforms that support innovation for global energy clients. Qualified candidates will bring strong engineering judgment, practical AI/ML deployment experience, and the ability to turn complex technical requirements into production-ready solutions.

  • Position Located in Houston, TX USA; Calgary, AB Canada; or Rio de Janeiro, Brazil
  • 8:00 a.m. – 5:00 p.m. Monday to Friday 
  • Full-Time position 
  • Hybrid Schedule Availability

The Company

Katalyst Data Management (KDM) is a global leader in subsurface data management solutions for the energy industry. For over 30 years, we have helped oil and gas companies, national governments, and energy organizations maximize the value of their data through secure storage, quality management, digital delivery, and online data marketing services. Our industry-leading iGlass™ platform provides customers with reliable, secure, 24/7 access to critical subsurface information, supported by robust system redundancy and data protection controls. Through innovation, technical expertise, and exceptional customer service, KDM continues to deliver trusted solutions to clients around the world.

Key Responsibilities and Accountabilities

Katalyst Data Management is seeking a Senior AI/ML Engineer to serve as a technical lead for segments of our AI innovation platform. This is a hands-on, high-impact role where you will own architecture and day-to-day development for AI projects that move from prototype to production.

You will work directly with the Director of Innovation and a small, high-velocity team to build, ship, and iterate AI capabilities that deliver real value to leading oil and gas clients worldwide. This is not a research-only role; it requires sound architectural judgment, practical execution, and the ability to deliver production-ready solutions in a rapidly evolving technology landscape.

The position may be based in Rio de Janeiro, Brazil; Houston, Texas; or Calgary, Alberta. We value adaptability and intellectual curiosity over mastery of any single technology stack, and we are especially interested in candidates who have repeatedly learned new tools quickly, made thoughtful technical decisions under uncertainty, and shipped AI/ML solutions that work in production.

Key Responsibilities:

  • Operate, scale, and optimize production GPU environments supporting AI workloads, including inference/model serving, OCR and vision models, embeddings, and large-scale document ingestion.
  • Lead the design and implementation of production AI/ML services that support intelligent search, classification, retrieval, and natural language interfaces for subsurface and E&P data.
  • Own technical architecture for core platform components, including retrieval systems, orchestration, model serving, and data pipelines, while balancing reliability, cost, security, and delivery speed.
  • Build, maintain, and optimize retrieval systems using relational databases, full-text search, and search or analytics platforms such as Elasticsearch/OpenSearch.
  • Develop and maintain RAG-style pipelines, including embeddings, vector search, hybrid retrieval, reranking, grounding, and evaluation against real customer workflows.
  • Integrate LLM APIs and agentic tooling into end-to-end applications, including prompt design, tool/function calling, evaluation, and production guardrails.
  • Support deployment, observability, alerting, incident response, and CI/CD practices across on-premises and cloud environments.
  • Partner with product leaders, business stakeholders, data experts, and domain specialists to translate ambiguous problems into clear technical plans, milestones, and measurable outcomes.
  • Establish and uphold engineering standards for code review, testing, documentation, design reviews, and operational excellence.
  • Mentor and provide technical guidance to engineers as the platform evolves.

Required Qualifications

  • Bachelor’s degree in computer science, Engineering, Data Science, or a related field, or equivalent practical experience.
  • 5+ years of professional software engineering experience, including 3+ years building and operating ML/AI-enabled applications in production.
  • Demonstrated experience designing and supporting end-to-end services, including APIs, data pipelines, model integration, observability, deployment, and operations.
  • Hands-on experience delivering search or information retrieval features, including full-text search, ranking/relevance, indexing strategy, and performance optimization.
  • Experience working in cloud environments and shipping containerized services using CI/CD practices.
  • Strong English communication skills, both oral and written, are required.

Skills Required:

  • Strong programming skills in Python preferred and/or Node.js, including writing clean, testable code and reviewing others’ code.
  • Strong SQL and relational database experience, including advanced querying, schema design awareness, full-text search, and performance tuning.
  • Experience with search and analytics platforms such as Elasticsearch/OpenSearch or equivalent.
  • Practical experience integrating LLM APIs into applications, including prompting patterns, tool/function calling, basic evaluation, and production guardrails.
  • Comfort working with modern AI development workflows, including agentic coding tools such as Claude Code or Codex to accelerate delivery while maintaining quality.
  • Working knowledge of cloud services and security fundamentals, including IAM concepts, secrets management, and network boundaries.
  • Strong English communication skills, both oral and written, with the ability to explain complex technical concepts clearly to technical and non-technical stakeholders.
  • Ability to translate ambiguous business needs into clear technical plans, trade-offs, and deliverables.

Preferred Qualifications & Skills 

  • Oil and gas industry experience or domain knowledge, including well data, seismic data, or regulatory documents.
  • Experience with GPU-accelerated workloads and the NVIDIA ecosystem.
  • Background in OCR pipelines and large-scale document processing.
  • Familiarity with vision-language models for document understanding.
  • Experience with agent-to-agent or multi-agent AI system patterns.
  • Patent, publication, or conference presentation experience in ML/AI.

Work Environment: 

This role is based in a professional office setting with routine use of computers and collaboration tools. Work is highly technical and team-oriented, involving close coordination with Cloud, Infrastructure, and Software Engineering teams. The environment emphasizes automation, scalability, and security, with frequent virtual meetings and occasional cross-functional project work.

Physical Demands:

This is primarily a sedentary role, involving extended periods of computer work. Occasional tasks may include setting up equipment, organizing supplies, or preparing meeting spaces, which could require light lifting, bending, or standing as needed.

Position Type and Expected Hours of Work: 

This is a full-time position. As a full-time position, the Senior AI/ML Engineer is eligible to participate in benefits coverage offered to Katalyst employees based on geographical location.

Monday through Friday, 8:00 a.m. to 5:00 p.m., with occasional extended hours to support deployments or maintain service continuity

Travel: 

Minimal travel may be required for on-premises infrastructure support, implementation, or occasional team collaboration. If participation in an offsite meeting is requested, all related travel expenses will be covered or reimbursed, in accordance with the company’s policies and local regulations.