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Training Airflow - Orchestrating Complex Data Pipelines

Ref: WXV675
10 people max.
5500€ HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
5 journées
in-person

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Learning objectives

  • Master Airflow's distributed architecture to scale professional enterprise data pipelines
  • Develop complex DAGs with custom operators, sensors, and advanced XComs for certifiable skills
  • Integrate Airflow with Kafka, Spark, and Kubernetes to orchestrate robust ETL processes
  • Optimize Airflow performance, monitoring, and alerting in critical environments
  • Implement CI/CD, backfill, and retry strategies for reliable data workflows
  • Design high-availability architectures tailored to enterprise needs
  • Deploy Airflow in production with advanced security and data governance

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 1Advanced Airflow Architecture: Distributed Scaling and High Availability (Celery, Kubernetes)

Dive into Airflow deployment on Kubernetes with CeleryExecutor, configure scalable workers and redundant schedulers, perform practical exercises on multi-node clustering, test fault tolerance via crash simulations, produce a deliverable architecture diagram with performance metrics, integrate initial Kafka hooks for real enterprise data pipelines.

Module 2Complex Airflow DAGs: Custom Operators, Sensors, and Advanced Patterns (Optimized ETL)

Design dynamic DAGs with TaskGroups and SubDAGs, implement custom Python operators for specific data transformations, deploy advanced sensors for external dependencies, chain exercises on conditional branching and intelligent retries, generate reusable templates for professional ETL pipelines, analyze real enterprise cases with secure XComs and extended logging.

Module 3Airflow Integrations: Kafka, Spark, and Data Engineering Tools (Hybrid Pipelines)

Couple Airflow with Kafka for real-time data streaming via KafkaProducerHook, orchestrate Spark jobs with SparkSubmitOperator in cluster mode, configure secure and idempotent connections, practice labs on end-to-end ETL pipelines with data lakes, test Kafka-Spark failure resilience, produce a complete deliverable workflow integrating Airflow as the central enterprise orchestrator.

Module 4Airflow Monitoring and Optimization: Performance and Alerting (Production Metrics)

Install Prometheus and Grafana for custom Airflow dashboards, optimize slot pools and parallelism for load peaks, implement Slack/PagerDuty alerts on SLAs, analyze bottlenecks via Flower and advanced logs, perform benchmarks on massive datasets with Spark, generate deliverable optimization reports, apply best practices for reduced cloud costs in professional data pipelines.

Module 5Production Airflow Deployment: CI/CD, Security, and Governance (Expert Best Practices)

Automate CI/CD with GitHub Actions and Kubernetes Helm charts, secure DAGs with RBAC and secrets backend, manage massive backfills and pool quotas, deploy via Helm on EKS/GKE, test DR scenarios with blueprints, finalize a capstone project on a complete Kafka-Spark-Airflow ETL pipeline, obtain code audit and certifying governance plan for critical enterprise environments.

Evaluation method

  • Advanced technical MCQ on architecture and integrations (80% pass threshold)
  • Capstone project: complete Kafka-Spark-Airflow ETL pipeline deployment
  • Peer code review and oral defense of technical choices

Learning method

  • 70% hands-on: real labs on Kubernetes clusters with production-like datasets
  • Enterprise case studies: pipeline failures analyzed and resolved
  • Individual mentoring: real-time feedback on custom DAG code
  • Post-training support: 3 months Slack access and resource updates

Methods, materials and delivery

The Training Airflow - 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 Airflow - 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 Airflow - 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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