Analytics Engineering with dbt Corporate Training
Learn to model, test, document, and ship trusted datasets with dbt in live guided labs.
Edstellar, a corporate training company, delivers corporate training that helps your team learn to build reliable analytics pipelines with dbt. Employees develop data modeling fluency, automated testing habits, and clear documentation practices through guided labs led by practitioners. Each session is tuned to your warehouse, tools, and workflows.
Instructor-led group trainingVirtual / on-site / off-site10 languagesDelivered inEnglish, Spanish, Mandarin, German, Arabic, Portuguese, Hindi, French, Japanese, Italian100+ countriesWe have delivered inUnited States, United Kingdom, India, Canada, Germany, France, Netherlands, UAE, Saudi Arabia, Singapore, Australia, Japan, Brazil, South Africa and 90+ more countries
How we build a confident analytics engineering team
EDSTELLAR ANALYTICS ENGINEERING CAPABILITY MODEL
Assess analytics capability
Skill checks map your team's SQL, modeling, and dbt baseline before training begins.
Set shared standards
One shared playbook for dbt project structure, naming, tests, and documentation.
Practice in guided labs
Labs cover modeling, Jinja macros, incremental builds, and CI pipelines for dbt.
Measure the lift
Lab reviews benchmark each employee's analytics engineering capability after training.
Scale across teams
One standard rolls out across datasets, dashboards, and teams with confidence.
Need more than one program?Get a group quote
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Program Overview: What is Analytics Engineering with dbt?
Analytics Engineering with dbt is a 24-hour, hands-on program for data and analytics engineers who build the models business teams trust. It covers dbt setup, modeling layers with refs, tests and docs, sources, seeds, snapshots, Jinja and macros, incremental models with performance tuning, and dbt Cloud CI pipelines. Participants practice the full workflow from raw sources to tested, deployed models.
Training is hands-on: most of the 24 hours is spent building dbt projects in guided labs, from setup to the end-to-end capstone. An instructor coaches each lab, reviewing your models, tests, and macros with feedback on clean, reliable pipeline practices. Three practice sessions target the hardest skills: reusable Jinja macros, incremental model design, and performance tuning. The five-hour capstone has you build a complete, documented, CI-tested dbt project ready for deployment.
Without disciplined modeling, SQL sprawl and undocumented transformations pile up, dashboards drift out of agreement, and every incident becomes a fire drill. The program teaches teams to replace that chaos with version-controlled models, automated tests, and documented sources. Participants learn to ship changes through CI, debug failures confidently, and keep performance steady as data grows.
They ship a dbt project the way a real team would: modeled, tested, documented, and presented. Your analytics engineers stop building fragile pipelines and start building ones nobody is afraid to touch.
Six modules and 24 hours: dbt setup, modeling, testing and documentation, Jinja and macros, incremental models, and CI with orchestration. Every module pairs concepts with a guided lab, so each technique is practiced. It closes with a capstone build the team models, tests, documents, and presents. Delivery is hybrid across virtual and onsite sessions, scheduled around your calendar. Cohorts train as one group or split into batches, with session materials and lab guides included for every participant.
What's Included in this Workshop for Your Enterprise Teams
- 1
dbt project setup
Configure a dbt project against your warehouse safely.
- 2
Modeling labs
Build staging, intermediate, and mart layers.
- 3
Testing and docs
Add tests and documentation to every model.
- 4
CI pipeline labs
Ship dbt through automated checks.
- 5
Capstone build
Model and document a full pipeline end to end.
- Instructor-led delivery across virtual, onsite, and hybrid
- Guided labs in every module with instructor coaching
- Capstone analytics build, reviewed with your team
- Flexible scheduling around your calendar
- Lab guides and reusable dbt templates included
- Group size and batches set along with you
Build your team's skills. Anywhere in the world.
Real-world use cases
from day one
Instructor-led training
for your teams
Delivered globally
in 100+ countries
Enterprise Training Solutions Customized for Your Company
One partner for instructor-led corporate training, delivered the way your teams work.
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Analytics Engineering with dbt Course Topics and Program Outline
A tailored 24-hour, six-module workshop: one learning journey from dbt setup to a capstone analytics build. Sessions pair concepts with labs on real-world use cases. Materials include lab guides and templates, plus a capstone assessment.
Built by Edstellar with analytics engineers
Built by practitioners who ship dbt pipelines in production, shaped around your stack and use cases.
Skill checks baseline your team's SQL fluency, modeling habits, and dbt experience before training begins.
Live instruction covers dbt setup, project structure, and the model-first workflow across 3 focused hours.
Guided labs build modeling, testing, macro, and performance skill across 12 hours of supervised practice.
Your team ships a tested, documented dbt pipeline in 9 hours, reviewed against production standards.
From dbt setup to a capstone analytics build, every technique is practiced in guided labs.
Delivered as
Delivered as a hybrid program of live instruction and guided labs, scheduled around your team's calendar in flexible batches.
Configure a dbt project against a sample warehouse, then build and run your first modeled layer in a guided walkthrough.
learna)Installing dbt Core and configuring profiles
b)Warehouse connections and safe development schemas
c)Project structure: models, seeds, snapshots, and docs
d)The ref and source workflow for model lineage
Model a sales dataset into layered marts, add tests to each model, and publish a documentation site for review.
practicea)Staging, intermediate, and mart layering patterns
b)Writing clean, reviewable model SQL
c)Generic and singular tests on every model
d)Auto-generated documentation with dbt docs
Add source freshness checks, snapshot a changing dimension, and write a macro that standardizes date spine logic.
practicea)Declaring sources and freshness checks
b)Seeds for reference data and snapshots for history
c)Jinja templating for dynamic SQL
d)Writing and packaging reusable macros
Convert a full-refresh model to incremental, tune it against large sample data, and benchmark the run time improvement.
practicea)Incremental strategies: append, merge, and delete-insert
b)Partitioning and clustering for warehouse performance
c)Diagnosing slow models with run artifacts
d)Balancing freshness, cost, and reliability
Wire a CI pipeline that builds and tests changed models on every pull request, then schedule a production job.
applya)Git workflows and pull request reviews for dbt
b)CI jobs: build, test, and slim CI on every PR
c)Job scheduling and environment separation
d)Alerting, lineage, and run monitoring
Build, test, and document a full dbt pipeline end to end, then present it for instructor review.
applya)Scoping the build: sources, marts, and consumers
b)Modeling and testing the full pipeline
c)Documentation and lineage for stakeholders
d)Capstone review and production readiness checklist
Customize this program tailored to your team?
Tell us your training needs: what your team already works with, the level they’re at, and the topics you want them to focus on. We’ll adjust the modules, duration and hands-on labs, and send you a customized outline for your group.
Key Skills and Outcomes Your Team Will Gain
Seven job-ready outcomes your team will demonstrate by the end of the program. Each competency is practiced in guided labs and reviewed in the capstone build.
Configure dbt projects
Set up dbt projects with safe profiles, development schemas, and version-controlled project structure.
Model layered datasets
Build staging, intermediate, and mart layers with clean ref chains and readable, reviewable SQL.
Test every model
Apply generic and singular tests so data quality issues surface before stakeholders see them.
Document with dbt docs
Publish auto-generated documentation and lineage that business users can actually navigate.
Write Jinja macros
Replace copy-paste SQL with reusable Jinja macros and packages that standardize team patterns.
Tune incremental pipelines
Use incremental strategies and warehouse-aware tuning to keep large pipelines fast and affordable.
Ship dbt through CI
Run dbt through pull request checks and scheduled jobs with monitoring, lineage, and alerting.
Teams that Benefit from this Analytics Engineering with dbt Group Training
This group training is built for analytics and data teams who want trusted, tested, and documented datasets without bottlenecks. Content adapts to each cohort's roles, warehouse, and experience, so every batch practices the workflows it owns, from first model to production pipeline.
Standardize pipelines with dbt conventions your team owns.
Give data engineers a shared dbt standard for modeling, testing, and CI that replaces one-off scripts.
Workflow friction
- Inconsistent SQL across teams
- Untested models reaching dashboards
- Slow, expensive pipeline runs
How the program helps
- Shared dbt project conventions
- Faster, reviewable model code
- Fewer late data quality surprises
Practice use cases
- dbt migration
- Model refactoring
- CI for data
Level up modeling craft with advanced dbt practice.
Help analytics engineers master Jinja, incremental strategies, and performance tuning on real workloads.
Workflow friction
- Copy-paste SQL sprawl
- Full-refresh jobs timing out
- Tribal knowledge, no docs
How the program helps
- Advanced modeling patterns
- Reusable macro libraries
- Measurable pipeline speedups
Practice use cases
- Macro design
- Incremental tuning
- dbt Cloud adoption
Ship dashboards on datasets teams can trust.
Enable BI teams to build dashboards on tested, documented marts instead of fragile extracts.
Workflow friction
- Dashboard numbers that disagree
- No lineage when figures break
- Manual extracts and rework
How the program helps
- Trusted, documented marts
- Faster dashboard delivery
- Clear lineage for audits
Practice use cases
- Mart design
- Metric definitions
- Dashboard readiness
Scale self-service with governed dbt standards.
Support data enablement teams rolling out self-service analytics on governed, well-tested models.
Workflow friction
- Shadow datasets everywhere
- Conflicting metric definitions
- New hires lost in the stack
How the program helps
- Governed self-service layers
- Consistent metric logic
- Onboarding-ready docs
Practice use cases
- Self-service marts
- Metric governance
- Team onboarding
Cohorts train as a cross-functional workforce, with each small group aligned on shared modeling and review standards.
Prerequisites: This program benefits data analysts, analytics engineers, and BI developers who build or support datasets for decision making. Basic SQL helps but is not required, and no prior dbt experience is needed. Content adapts to each cohort's warehouse, tools, and experience so every team practices the workflows it owns.
Data Analyst to Analytics Engineering Lead
Start with dbt setup and layered modeling, then advance through testing, macros, and performance tuning to full CI delivery and pipeline ownership across the data stack.
A program that grows with analytics careers, from first dbt model to confident pipeline ownership.
Mixed cohort, or several teams at once?
We can tailor the training to different teams, roles, and experience levels within the same program.
Certificate of Training Completion.
On successful completion, employees receive an Edstellar course completion certificate, recognizing their commitment to ongoing learning and professional development. It validates the skills they have built and motivates them to keep growing and contribute to organizational success.
Earned, not attended. Awarded on completion of all hands-on labs and the capstone project.
Training Delivery Modes: Virtual, Onsite and Hybrid
Recordings and lab guides are shared on your LMS so the team can revisit each module after the live sessions.
Hybrid Training
Instructor-led sessions mix onsite and virtual delivery with guided labs throughout. Teams build dbt pipelines on real data while the instructor coaches and reviews models. Hybrid keeps scheduling flexible without losing live interaction.
- Live instruction across onsite and virtual sessions
- Guided labs with instructor coaching and model reviews
- Real dbt workflows on your warehouse and data
- Flexible scheduling without losing live interaction
Onsite Training
Instructor-led training at your offices, with labs set up on your warehouse and tooling. The instructor pairs with the team in person, reviews models together, and tunes exercises to your stack and workflows.
- Instructor-led training at your offices
- Labs set up on your warehouse and tooling
- In-person pairing and model reviews
- Exercises tuned to your stack and workflows
Live Virtual Training
Live virtual sessions on Zoom or Teams with screen-shared pairing, breakout labs, and real-time model review. Your team gets the same guided labs and instructor coaching as onsite, from anywhere.
- Live virtual sessions on Zoom or Teams
- Screen-shared pairing and breakout labs
- Real-time model review with the instructor
- Same guided labs as onsite, from anywhere
Need a training format that works for your team?
Full days, half days across weeks, or split by module. Tell us the delivery window and we schedule the cohort around it.
Frequently Asked Questions
Share your team size, timelines, and delivery preference, and we will send a detailed per-group quote with batch options.
Yes. Book a discovery call and we will map your warehouse, dbt usage, and goals to a tailored training plan before you commit.
Yes. Live virtual sessions run on Zoom or Teams with the same guided labs and instructor coaching as onsite delivery.
Yes. The instructor runs the full program at your offices, with labs set up on your warehouse and tooling for realistic practice.
The program runs 24 hours of instructor-led training, usually across three to six days or weekly sessions on a flexible, mutually agreed schedule.
Question not answered here?
Put it in the request. A training specialist answers it directly, within one business day.
Where this Training Fits in Your Team's learning path.
Analytics engineering with dbt comes third, after SQL and dimensional modelling. dbt is mostly SQL organised into models, so both foundations need to be in place before your team builds with it. Once models are in production, DataOps practice keeps the pipelines reliable as they grow.
Why Choose Edstellar as Your Analytics Engineering with dbt Corporate Training Provider
Edstellar pairs instructor-led delivery with hands-on dbt labs so your analytics teams leave with working pipelines, not just theory.
EXPERT TRAINERS
YEARS DELIVERING
ORGANIZATIONS TRAINED
CERTIFIED
Tailored
Every cohort's labs and examples are tailored to your warehouse, dbt setup, and modeling standards.
Proven Methodology
A field-tested methodology moves your team from first dbt model to tested, documented pipelines.
Practice-Based Learning
Guided labs in every module turn dbt concepts into practiced skill on real data.
Expert Trainers
Learn from analytics engineers who ship dbt pipelines in production every day.
Global Scale
One consistent program delivered across your regions, time zones, and analytics teams.
Measurable Outcomes
Lab checkpoints and capstone reviews show exactly what each employee can build and ship.
Also from Edstellar
Talent assessments
Psychometric, behavioral, leadership and 360-degree assessment.
→Training needs analysis
Needs analysis, gap identification, and a training roadmap.
→L&D consulting
Learning strategy, content, technology and ROI measurement.
→OD consulting
Org design, succession planning and cultural change.
→Managed training services
Training outsourcing, vendor management, logistics and administration.
→Coaching solutions
Executive and manager coaching that keeps skills in use.
Start an RFP shaped to your needs.
Answer three quick questions about team size, scope, and how often you need the program run, then send the request from the last step. Everything you choose travels with it, so you only fill this in once.
How many team members need training?
Analytics Engineering with dbt Training Packages & Pricing
Where L&D holds an annual budget, license packages price the whole year at once instead of raising a purchase order per workshop. Hours and licenses are pooled across teams, programs and locations, so unused capacity is not stranded in one department.
Starter
120
trainee licenses64 hours of group training
Tailored for SMBs
Growth
320
trainee licenses160 hours of group training
Ideal for growing SMBs
Enterprise
800
trainee licenses400 hours of group training
Designed for large corporations
Custom
Unlimited
trainee licensesDuration set by the rollout
Multi-region and multi-year
Training Packages & Pricing
Choose the training format that works for your team. Pricing is customized based on your requirements, cohort size, and delivery needs.
Request Analytics Engineering with dbt Training for Your Team
Share your team size, warehouse, dbt usage, and timelines to receive a tailored training plan and quote. Book a discovery call to discuss your goals; we confirm availability and respond with a proposal.