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Training Dagster - Orchestrating Complex Data Pipelines

Ref: LRP513
10 people max.
$6,600 HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$180/day onsite · +$540 with certification exam
5 days
in-person

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Learning objectives

  • Master the advanced architecture of Dagster for professional data pipelines
  • Develop complex graphs and reusable assets in a certifying training
  • Optimize Dagster performance in enterprise environments
  • Implement monitoring and backfill strategies for expert skills
  • Design scalable Dagster deployments on Kubernetes and cloud
  • Integrate Dagster into data ecosystems to boost team productivity
  • Acquire Dagster skills certification for a data engineering career

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

Don't let this gap widen

Why this program matters

  • Without this upskilling, your team accumulates a technological gap that translates directly into productivity loss.

  • Organizations that don't train their talents on key topics see their competitiveness drop.

  • Every quarter without training is a gap widening with competitors who invest.

  • The cost of inaction quickly exceeds that of well-targeted training.

Allan Busi
Allan Busi

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1Dagster Architecture: Advanced Asset and Graph Modeling (Dagit, CLI, YAML)

Dive into expert Dagster concepts via Dagit to visualize complex graphs, model interdependent data assets with practical exercises on real datasets, configure CLI for fast local executions, generate YAML for scalable definitions, analyze common error patterns, produce a first modular pipeline deliverable by end of day, strengthening professional skills in data orchestration.

Module 2Dagster Executors: Performance and Resource Optimization (Celery, Kubernetes)

Explore advanced Dagster executors like Celery for massive parallelism, integrate Kubernetes for horizontal scaling on cloud clusters, test configurations with intensive workloads, measure latencies and CPU via built-in metrics, debug memory leaks in live coding, deploy a customized executor, obtain deliverable: optimized blueprint for enterprise pipelines, boosting expert data engineering efficiency.

Module 3Dagster Monitoring: Alerts, Backfills, and Observability (Sensors, Materializations)

Configure Dagster sensors for intelligent event-driven triggers, implement massive backfills on historical data, integrate observability with Prometheus/Grafana for custom dashboards, simulate Slack/Email alerts on failures, analyze materializations for fine-grained traceability, practice on real e-commerce cases, produce complete monitoring report as deliverable, perfecting skills in professional pipeline reliability.

Module 4Dagster Integrations: Spark, DBT, Airflow Migration (IO Managers, Hooks)

Master Dagster IO Managers for advanced S3/Postgres persistence, integrate Spark jobs into native graphs, migrate Airflow DAGs to Dagster with automated tools, hook DBT models for modern ELT, test interoperability on large datasets, manage secrets via Dagster secrets, deploy hybrid pipeline integrating legacy tools, deliverable: production-ready migration blueprint, accelerating enterprise data adoption.

Module 5Dagster Deployment: Helm Charts, CI/CD, and Production Scaling (Dagster Cloud)

Deploy Dagster to production via Helm on Kubernetes, automate CI/CD with GitHub Actions/ArgoCD, scale with hybrid Dagster Cloud, simulate extreme loads for resilience, configure multi-tenancy for teams, conduct pair-programming code review on personal projects, finalize portfolio with end-to-end deployed pipeline, obtain expert skills certification, ready for enterprise data engineering challenges.

Evaluation method

  • Advanced technical quiz on Dagster architecture and executors
  • Capstone project: complete scalable pipeline with monitoring
  • QCM evaluation and peer-review for Qualiopi certification

Learning method

  • 100% hands-on with progressive exercises on real datasets
  • Concrete use cases inspired by Fortune 500 production environments
  • Supervision by certified Dagster experts (5:1 ratio)
  • Post-training resources: Git repo, replay videos, Slack community

Methods, materials and delivery

The Training Dagster - Orchestrating Complex Data Pipelines program is delivered onsite or remote (blended-learning, e-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.

The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.

Equipment required

For the smooth delivery of the Training Dagster - Orchestrating Complex Data Pipelines program, the following equipment is required:

  • Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
  • Training environments installed on workstations or accessible online
  • Course materials, hands-on exercises and complementary resources
  • Post-training access to materials and educational resources

For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.

* contact us for remote delivery feasibility** ratio varies depending on the program

Skills assessment methods

Assessment of skills acquired during the Training Dagster - Orchestrating Complex Data Pipelines program is performed through:

  • During training: case studies, hands-on labs and professional scenarios
  • End of training: self-assessment questionnaire and skills evaluation by the trainer
  • After training: completion certificate detailing acquired skills

Program accessibility

Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.

Enrollment terms and lead times

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
Our method

Training quality, guaranteed at every step

Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.

Step 1

Rigorous trainer selection

Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.

  • Triple validation: technical, pedagogical, sectoral.
  • Minimum rating 4.8/5 over the last 12 sessions.
Step 2

You meet the trainer beforehand

30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.

  • Live briefing on goals and team context.
  • Veto right — we swap the trainer for free if needed.
Step 3

Content tailored to your context

No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.

  • Hands-on cases drawn from your stack and projects.
  • Program co-written then validated by your team.
Step 4

Continuous quality follow-up

Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.

  • NPS, knowledge quizzes and skills self-assessment.
  • Satisfaction guarantee: fully satisfied or free rework.

A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

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