Data Elephant was founded in 2022 to fulfill a need in the Canadian market for a dedicated and full-stack data and analytics services firm.
Our founders bring technology services experience from boutique and global consulting firms resulting in a unique engagement model and value proposition for our clients.
Our approach is to bring the deep technical expertise, flexibility, and drive to prove value quickly of a boutique firm, and combine it with the strategic thinking, proven methodology, and cross-industry experience of a global firm.
Our goal is to be our client's go-to Canadian partner for driving value and impact across the whole data stack.

Data Elephant

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data-analyst

Data Elephant is a Vancouver-based data and analytics consultancy founded in 2022 that helps organizations modernize data infrastructure and platforms to enable self-service reporting, advanced analytics, AI, and machine learning. They offer end-to-end services including data strategy, cloud migration, data engineering (warehouses, lakes, lakehouses), governance, BI, MLOps, and GenAI proof-of-concept and training, partnering with cloud and analytics providers like AWS, Databricks, and Microsoft. Data Elephant serves enterprise clients across industries (energy, mining, finance, transportation, retail, sports, public sector) and positions itself as a trusted advisor delivering measurable business outcomes through collaboration and long-term partnerships.

Data Elephant was founded in 2022 to fulfill a need in the Canadian market for a dedicated and full-stack data and analytics services firm.

Our founders bring technology services experience from boutique and global consulting firms resulting in a unique engagement model and value proposition for our clients. 

Our approach is to bring the deep technical expertise, flexibility, and drive to prove value quickly of a boutique firm, and combine it with the strategic thinking, proven methodology, and cross-industry experience of a global firm. 

Our goal is to be our client's go-to Canadian partner for driving value and impact across the whole data stack.

• Compare and reconcile large datasets across legacy and new Oracle databases
• Investigate approximately 7–10 million identified data discrepancies
• Perform root-cause analysis to determine why records and fields do not match
• Review Oracle SQL, PL/SQL, stored procedures, and legacy application logic
• Trace data from multiple source systems through Informatica and PL/SQL transformations
• Determine intended business rules and how individual fields should be populated
• Distinguish between source-data issues, transformation defects, mapping gaps, and logic differences
• Document findings, business rules, discrepancy patterns, and recommended resolutions
• Work with business stakeholders to validate data expectations
• Collaborate with architects and developers to recommend fixes
• Support developers during remediation and validate implemented fixes
• Use AI-assisted analysis tools where appropriate
• Own assigned analysis and communicate findings to technical and business audiences

Data Analyst, Oracle

Senior Oracle Data Analyst reconciling millions of records for an oil and gas modernization initiative. Investigating legacy-to-new-system discrepancies and guiding remediation.

ai-engineer

• Design, build, and deploy end-to-end AI/ML solutions in production environments
• Develop robust backend systems and APIs to support AI-driven applications
• Build and maintain data pipelines and feature engineering workflows
• Implement and operationalize machine learning models (training, deployment, monitoring)
• Work with modern AI tooling (LLMs, agents, orchestration frameworks)
• Collaborate with clients to translate business problems into technical solutions
• Contribute to architecture decisions and best practices across projects
• Mentor client team members and contribute to internal capability building

Senior DBX AI/ML Engineer

Senior AI/ML Engineer building AI solutions for clients in industrial sectors. Collaborating on impactful projects with modern AI tooling and data pipelines.

data-engineer

• Design and implement conceptual, logical, and physical data models aligned to business requirements
• Develop dimensional models (star/snowflake schemas) for analytics and reporting use cases
• Define and manage data structures within Databricks (Delta Lake)
• Partner with business stakeholders to translate requirements into robust data models
• Work closely with data engineers to align modeling with ingestion and transformation pipelines
• Establish and enforce data modeling standards, naming conventions, and best practices
• Optimize data models for query performance and cost efficiency within Azure and Databricks
• Produce clear documentation for data models, definitions, and transformations

Senior Data Architect – Data Modelling

Senior Data Architect for Data Elephant designing and delivering scalable data models within cloud platforms. Collaborating with engineers and stakeholders to implement best practices in data modeling.

scrum-master

• Lead end-to-end delivery of data platform, analytics, ML, and GenAI initiatives
• Own project planning, scope, timelines, budgets, risks, and dependencies
• Translate high-level business goals into actionable delivery plans and milestones
• Proactively identify and manage delivery risks, trade-offs, and escalations
• Facilitate Agile ceremonies (stand-ups, sprint planning, reviews, retrospectives)
• Coach teams and clients on Agile best practices while adapting to real-world constraints
• Maintain and optimize backlogs in partnership with Product Owners and tech leads
• Communicate status, risks, and outcomes clearly and confidently
• Manage expectations and navigate shifting priorities without losing momentum
• Support proposal scoping and delivery planning during pre-sales as needed

Scrum Master/Project Manager

Senior Project Manager/Scrum Master leading data and analytics initiatives for clients. Overseeing project delivery with a focus on Agile practices and stakeholder management.

engineer

• Lead the implementation of modern data platforms and architectures on Databricks (including ETL, workload migrations, and Unity Catalog).
• Design and implement data pipelines using Azure Databricks (PySpark, SQL)
• Build and optimize batch and streaming data workloads
• Migrate legacy data workloads to Azure + Databricks
• Implement Delta Lake patterns (medallion architecture, CDC, data quality)
• Integrate Databricks with Azure services such as ADLS, ADF, Azure Key Vault and DevOps/Github
• Optimize performance and cost (cluster sizing, job orchestration, query tuning)
• Collaborate with solution architects, analytics engineers, and client stakeholders
• Support client enablement through knowledge transfer and documentation
• Provide hands-on solution delivery, including guiding and working closely with client engineers and ensuring best practices.
• Implement governance models and Unity Catalog including data access, lineage, and security frameworks.
• Evaluate and prioritize high-value AI and ML use cases, embedding Generative AI into client strategies.
• Act as a thought leader by contributing to client workshops, executive roundtables, and industry discussions.

Databricks Engineer

Senior Databricks Engineer responsible for designing and implementing modern data platforms on Azure Databricks. Working closely with client teams to migrate and optimize data workloads while ensuring best practices.

• Own and evolve Data Elephant’s delivery management framework for data, analytics, and AI projects
• Establish consistent practices for Agile Project Delivery, Project Planning, Backlog Management, Sprint Ceremonies, Requirements Management, User Stories, and Project Health Monitoring
• Ensure engagements are delivered with predictability, transparency, and high quality
• Establish and maintain strong Agile/Scrum practices across the organization, ensure agile practices are adapted appropriately for data and platform delivery projects
• Conduct delivery healthchecks in partnership with Account Delivery Lead across active engagements
• Support project teams in navigating delivery complexity while maintaining transparency and trust with clients
• Define best practices for delivering projects; introduce tools and frameworks that improve delivery visibility and success, and team coordination
• Help scale Data Elephant's ability to deliver multiple complex projects simultaneously
• Manage and mentor a team of Project Managers / Scrum Masters and Business Analysts and provide coaching on Agile practices, stakeholder management, delivery governance and consistency
• Hire and lead a team providing coaching, performance management, career progression, etc.
• Ensure team is delivering with consistency and in accordance to client expectations

Agile Delivery Lead

Agile Delivery Lead at Data Elephant, building a delivery management capability for data, analytics, and AI projects. Leading PMs, Scrum Masters, and BAs to ensure quality project execution.

Data Elephant was founded in 2022 to fulfill a need in the Canadian market for a dedicated and full-stack data and analytics services firm. Our founders bring technology services experience from boutique and global consulting firms resulting in a unique engagement model and value proposition for our clients. Our approach is to bring the deep technical expertise, flexibility, and drive to prove value quickly of a boutique firm, and combine it with the strategic thinking, proven methodology, and cross-industry experience of a global firm. Our goal is to be our client's go-to Canadian partner for driving value and impact across the whole data stack.

Data Elephant

About the company

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6 jobs found

Data Analyst, Oracle

Data Elephant

Senior DBX AI/ML Engineer

Data Elephant

Senior Data Architect – Data Modelling

Data Elephant

Scrum Master/Project Manager

Data Elephant

Databricks Engineer

Data Elephant

Agile Delivery Lead

Data Elephant