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Manager Data Engineering Jobs in British Columbia

... product management, design, engineering, Business Intelligence, and data science. You'll also lead the integration of these advanced AI systems into Alexa Audio's core capabilities, ensuring a ...

The Junior Data Technologist works within a team of Data Engineers to realize our mission ... All interviews and hiring decisions are being made by Kal Tire's hiring managers and recruiters.

Junior Data Technologist

Vernon, BC ยท On-site

CA$67K - CA$80K/yr

The Junior Data Technologist works within a team of Data Engineers to realize our mission ... All interviews and hiring decisions are being made by Kal Tire's hiring managers and recruiters.

Showing results 41-60

Manager Data Engineering information

See British Columbia salary details

$81.5K

$129.4K

$224.5K

How much do manager data engineering jobs pay per year?

As of Sep 7, 2026, the average yearly pay for manager data engineering in British Columbia 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 British Columbia?

The most popular types of Data Engineering jobs in British Columbia are:

What are popular job titles related to Manager Data Engineering jobs in British Columbia?

For Manager Data Engineering jobs in British Columbia, the most frequently searched job titles are:

What job categories do people searching Manager Data Engineering jobs in British Columbia look for?

The top searched job categories for Manager Data Engineering jobs in British Columbia are:

Infographic showing various Manager Data Engineering job openings in British Columbia as of August 2026, with employment types broken down into 93% Full Time, and 7% Temporary. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $129,416 per year, or $62.2 per hour.

Senior Business Analyst - Data & Analytics

Data Elephant Inc

Vancouver, BC โ€ข On-site

Contractor

This job post hasย expired today.ย Applications are no longer accepted.


Job description

WeareseekingaSeniorTechnicalBusinessAnalysttosupportalarge-scaledataandanalyticstransformationforaclient.


This role will bridge business subject matter experts and technical delivery teams. You will turn complex business and data needs into clear, approved and delivery-ready requirements that engineers, architects and analytics developers can confidently estimate and implement.

The successful candidate will bring strong technical data knowledge, excellent requirements-management discipline and deep experience structuring complex work into appropriately sized user stories. You will ensure the team builds what the business has requested, understands why it matters and can identify dependencies, blockers and acceptance criteria before work enters a sprint.


KeyResponsibilities

  • Lead requirements discovery sessions with business stakeholders, subject matter experts, data engineers, architects and analytics teams.
  • Translate business needs and subject matter expertise into clear, complete and technically actionable requirements.
  • Document current-state and future-state business processes, data flows, business rules and reporting requirements.
  • Develop detailed source-to-target data mappings, transformation rules and data definitions.
  • Analyze data to validate requirements, identify quality issues and clarify expected business outcomes.
  • Create high quality epics, features and user stories with clear acceptance criteria, technical context and measurable outcomes.
  • Breakcomplexinitiativesintoappropriatelysizedandsequencedstoriesthatdeliveryteamscanestimateandcompletewithinasprint.
  • Identify and document dependencies, assumptions, risks, blockers and required decisions.
  • Ensure requirements are reviewed, refined, approved and formally signed off before development begins.
  • Facilitate backlog refinement, sprint planning and requirements walkthroughs with delivery teams.
  • Maintain a delivery-ready backlog and help sequence work based on dependencies, priorities and team capacity.
  • Support engineering and analytics teams throughout delivery by answering questions and resolving ambiguity quickly.
  • Coordinatebusinessvalidation,useracceptancetestingandfinalstakeholderapproval.
  • Establish and promote consistent standards, templates and best practices for requirements and user-story development.
  • Help business stakeholders understand the reasoning behind proposed approaches, sequencing and requirements decisions.


RequiredExperience

  • Significant recent experience as a Senior Business Analyst, Technical Business Analyst o Data Business Analyst supporting modern data and analytics programs.
  • Strongunderstandingofmodernclouddataplatformsandanalyticalarchitectures.
  • Hands-on experience with data mapping, data analysis, data transformation requirements and source-to-target documentation.
  • Working knowledge of medallion architecture, including bronze, silver and gold data layers.
  • Demonstratedabilitytotranslatecomplexbusinessrequirementsintotechnicalworkthatdataengineers,BIdevelopersandarchitectscanimplement.
  • Extensive experience developing complex user stories, acceptance criteria, process flows and requirements documentation.
  • Strong understanding of Agile delivery, backlog management, story sizing, sprint readiness and dependency management.
  • Experience identifying gaps, challenging unclear requirements and driving decisions to closure.
  • Abilitytoproviderecent,relevantexamplesofcomplexuserstoriesandrequirementstemplatesthathavecontributedtosuccessfuldelivery.
  • Excellentfacilitation,communicationandstakeholder-managementskills.
  • Confidence working with senior stakeholders and highly experienced subject matter experts.


Thesuccessfulcandidatedoesnotneedtobeahands-ondeveloperbutmustunderstanddataandanalyticstechnologywellenoughtocommunicateeffectivelywithtechnicalteamsandproduceimplementation-readyrequirements.


PreferredQualifications

  • Experience supporting enterprise data transformations, cloud migrations or modern analytics implementations.
  • Experience in construction, engineering, infrastructure or another asset-intensive industry.
  • Familiarity with data governance, metadata management, data quality and business glossary practices.
  • Experienceworkingacrossdataengineering,governance,BIandbusinessworkstreams.
  • Relevantbusinessanalysis,Agileorproduct-managementcertificationisanasset.