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Hire Apache Airflow Developers & Consultants
Scale your data team with pre-vetted Apache Airflow developers. Our experts build production-grade DAGs, ETL pipelines, and data orchestration workflows—on AWS MWAA, Cloud Composer, or self-hosted Kubernetes.
4.9★ Clutch
ISO 27001
200+ Teams
In 48 HOURS
You'll Have
Pre-vetted Airflow experts ready to start
DAGs that run reliably in production
Pipelines that scale with your data
Replace or refund within 15 days
50+
Data Engineers
48hrs
Time to Hire
4.9/5
Client Rating
Trusted by data-driven organizations
Hire Expert Apache Airflow Developers for Your Data Team
Apache Airflow has become the industry standard for data pipeline orchestration—used by Airbnb, Spotify, Twitter, and thousands of data teams worldwide. But finding experienced Apache Airflow developers who can build reliable, production-grade DAGs is a challenge. The demand for Airflow talent far exceeds the available supply.
When you hire Apache Airflow developers through Tasrie, you get pre-vetted data engineers with hands-on experience building complex ETL pipelines, orchestrating workflows across AWS, GCP, and Azure, and deploying Airflow on Kubernetes at scale. Our engineers integrate directly with your team—attending standups, reviewing code, and owning pipeline reliability.
Whether you need dedicated Apache Airflow developers for ongoing pipeline work or Apache Airflow consultants for architecture reviews and optimization, we match you with the right talent in 48 hours—with a 15-day risk-free trial.
Why Hire Apache Airflow Developers Through Tasrie
Get expert Airflow talent without the months-long hiring process
Start in 48 Hours
Pre-vetted Airflow developers ready for immediate engagement. No months of recruiting—get pipeline expertise this week.
15-Day Risk-Free Trial
Not the right fit? Get a replacement or full refund within 15 days. Zero risk to evaluate your Airflow developer.
Production Experience
Our Airflow developers have built and maintained pipelines processing millions of records daily in production environments.
Full-Stack Data Skills
Beyond Airflow—our developers know Python, SQL, Spark, dbt, cloud platforms, and data warehouses for end-to-end pipeline delivery.
Cloud-Native Expertise
AWS MWAA, Google Cloud Composer, Astronomer/Astro—our developers deploy and manage Airflow on any cloud platform.
40-60% Cost Savings
Access senior Airflow talent at a fraction of local hiring costs. No recruitment fees, benefits overhead, or training expenses.
Apache Airflow Expertise You Can Hire
From DAG development to Airflow infrastructure—specialized talent for every need
Airflow DAG Development
Expert developers who design, build, and optimize complex DAGs for data pipeline orchestration with proper dependency management and error handling.
- Complex DAG architecture
- Task dependency design
- Dynamic DAG generation
- Idempotent task design
ETL/ELT Pipeline Engineering
Build production-grade ETL and ELT pipelines that extract, transform, and load data across databases, APIs, data lakes, and warehouses.
- Data extraction & ingestion
- Transformation logic
- Incremental loading
- Data quality checks
Cloud Airflow (MWAA/Composer)
Deploy and manage Airflow on AWS MWAA, Google Cloud Composer, or Astronomer with cloud-native best practices and cost optimization.
- AWS MWAA setup & management
- Google Cloud Composer
- Astronomer/Astro deployment
- Cloud cost optimization
Airflow Infrastructure & DevOps
Production Airflow deployments on Kubernetes with CeleryExecutor or KubernetesExecutor, auto-scaling workers, and GitOps-driven DAG deployment.
- KubernetesExecutor setup
- Helm chart deployment
- Worker auto-scaling
- GitOps DAG CI/CD
Data Warehouse Orchestration
Orchestrate data workflows across Snowflake, BigQuery, Redshift, and ClickHouse with Airflow operators, dbt integration, and scheduling.
- Snowflake/BigQuery integration
- dbt orchestration
- Data warehouse loading
- SLA monitoring
Airflow Migration & Upgrades
Migrate from legacy schedulers (Cron, Luigi, Oozie) to Airflow, or upgrade existing Airflow 1.x deployments to Airflow 2.x with zero downtime.
- Airflow 1.x to 2.x migration
- Cron/Luigi/Oozie migration
- DAG refactoring
- Zero-downtime upgrades
Flexible Hiring Models for Airflow Talent
Choose between dedicated developers, Apache Airflow consultants, or project-based engagements
Discovery Sprint
fixed‑price2–3 weeks to assess, prioritize, and plan quick wins with a roadmap.
- Architecture & pipeline review
- Risk/priorities report
- 90‑day roadmap
Fixed‑scope Project
from $15k+Defined deliverables with milestones and success criteria.
- Clear deliverables & timeline
- Enablement & docs included
- Outcome‑based KPIs
Senior Retainer
monthlyOngoing partnership for velocity, reliability, and enablement.
- Hands‑on architecture & reviews
- On‑call guidance for teams
- Quarterly roadmap & metrics
Technologies Our Airflow Developers Work With
End-to-end data stack expertise beyond just Airflow
Orchestration
- Apache Airflow 2.x
- AWS MWAA
- Google Cloud Composer
- Astronomer / Astro
Data Processing
- Apache Spark / PySpark
- dbt Core / dbt Cloud
- Pandas / Polars
- Apache Kafka
Data Warehouses
- Snowflake
- Google BigQuery
- Amazon Redshift
- ClickHouse
Cloud Platforms
- AWS (S3, Glue, EMR, MWAA)
- GCP (GCS, Dataproc, Composer)
- Azure (ADLS, Synapse, ADF)
- Databricks
Infrastructure
- Docker & Kubernetes
- Terraform / Helm
- GitHub Actions / GitLab CI
- Prometheus / Grafana
Databases & Storage
- PostgreSQL / MySQL
- MongoDB / DynamoDB
- Delta Lake / Iceberg
- Elasticsearch
How to Hire Apache Airflow Developers
A simple 4-step process to get expert Airflow talent on your team
- 1
Share Your Requirements
Tell us about your data pipelines, tech stack, Airflow version, cloud platform, and team structure. We understand your orchestration challenges to find the right Airflow developer.
- 2
Review Matched Candidates
Within 24-48 hours, receive profiles of pre-vetted Apache Airflow developers matching your requirements. Review portfolios, conduct technical interviews, and select your preferred candidates.
- 3
Start Risk-Free Trial
Your chosen Airflow developer starts working with your data team immediately. Evaluate DAG quality, communication, and cultural fit during the 15-day trial period.
- 4
Scale Your Data Team
Continue with your dedicated Airflow developer or add more data engineers as pipeline complexity grows. Scale up for migrations, scale down after delivery—full flexibility.
Why Hire Apache Airflow Consultants from Tasrie
What sets our Airflow talent apart from freelancer platforms
Production Airflow Experience
Engineers who've run Airflow at scale, not just tutorials
Full Data Stack Expertise
Python, SQL, Spark, dbt, cloud—not just Airflow
No Lock-in
15-day trial, flexible terms, transparent pricing
Direct Communication
Work with your engineer directly, no middlemen
Hiring Airflow Developers: Tasrie vs Alternatives
See why data teams choose Tasrie over freelancer platforms
| Factor | Tasrie | Freelancer Platforms |
|---|---|---|
| Vetting Process | Technical + production checks | Self-reported profiles |
| Trial Period | 15-day risk-free | No guarantee |
| Replacement | Free replacement | Start over |
| Team Integration | Full-time dedication | Split across clients |
| DevOps Support | Airflow infra included | DAG development only |
| Consulting Option | Architecture + hands-on | Hands-on only |
What makes us different
We're not a typical consultancy. Here's why that matters.
No vendor bias
No commissions, no referral incentives, no behind-the-scenes partnerships. We stay neutral so you get the best option — not the one that pays.
Engineering-first, not sales-first
All engagements are led by senior engineers, not sales reps. Conversations are technical, pragmatic, and honest.
Technology chosen on merit
We help you pick tech that is reliable, scalable, and cost-efficient — not whatever is hyped or expensive.
Built around your real needs
We design solutions based on your business context, your team, and your constraints — not generic slide decks.
What Clients Say About Our Data Engineers
See why data teams trust us to hire Apache Airflow developers
"Their team helped us improve how we develop and release our software. Automated processes made our releases faster and more dependable. Tasrie modernized our IT setup, making it flexible and cost-effective. The long-term benefits far outweighed the initial challenges. Thanks to Tasrie IT Services, we provide better youth sports programs to our NYC community."
Anthony Treyman
Kids in the Game, New York
"Tasrie IT Services successfully restored and migrated our servers to prevent ransomware attacks. Their team was responsive and timely throughout the engagement."
Rose Wang
Operations Lead
"Tasrie IT has been an incredible partner in transforming our investment management. Their Kubernetes scalability and automated CI/CD pipeline revolutionized our trading bot performance. Faster releases, better decisions, and more innovation."
Shahid Ahmed
CEO, Jupiter Investments
"Their team deeply understood our industry and integrated seamlessly with our internal teams. Excellent communication, proactive problem-solving, and consistently on-time delivery."
Justin Garvin
MediaRise
"The changes Tasrie made had major benefits. Fewer outages, faster updates, and improved customer experience. Plus we saved a good amount on costs."
Nora Motaweh
Burbery
Our Industry Recognition and Awards
Discover our commitment to excellence through industry recognition and awards that highlight our expertise in driving DevOps success.
FAQs About Hiring Apache Airflow Developers
Common questions about hiring Airflow developers and consultants
How quickly can I hire an Apache Airflow developer?
You can have a vetted Apache Airflow developer working on your project within 48-72 hours. We maintain a pre-screened pool of Airflow specialists with hands-on production experience. For niche requirements like Airflow + Spark or Airflow + dbt, matching may take up to 1 week.
What skills do your Apache Airflow developers have?
Our Airflow developers are proficient in: Python (advanced), DAG design and optimization, custom operators/hooks/sensors, ETL/ELT pipeline development, cloud platforms (AWS MWAA, Google Cloud Composer, Astronomer), Kubernetes deployment, SQL and data warehouses (Snowflake, BigQuery, Redshift), and CI/CD for DAG deployment.
What is the cost to hire an Apache Airflow developer?
Dedicated Apache Airflow developers start from $5,000/month for mid-level engineers and $7,000-$10,000/month for senior specialists. Apache Airflow consultants are available on hourly rates from $45-$75/hour. We provide transparent pricing with no hidden fees or recruitment charges.
Do you offer Apache Airflow consulting services?
Yes. Our Apache Airflow consultants provide architecture reviews, performance optimization, migration planning, best practices audits, and team training. Whether you need a one-time assessment or ongoing advisory, our consultants help you build production-grade data pipelines.
Can your developers migrate us from Cron jobs or Luigi to Airflow?
Yes. We specialize in migrating from legacy orchestrators (Cron, Luigi, Oozie, custom scripts) to Apache Airflow. Our migration process includes workflow mapping, DAG development, parallel running, testing, and cutover with zero data pipeline disruption.
Do your Airflow developers have cloud platform experience?
Yes. Our Apache Airflow developers have hands-on experience with AWS MWAA (Managed Workflows for Apache Airflow), Google Cloud Composer, and Astronomer/Astro. They can deploy, manage, and optimize Airflow on any cloud platform or self-hosted Kubernetes environments.
Can you help with Airflow 1.x to 2.x migration?
Absolutely. Migrating from Airflow 1.x to 2.x involves DAG API changes, import path updates, operator refactoring, and database migration. Our developers handle the full migration with proper testing, rollback plans, and zero-downtime cutover strategies.
What industries do your Apache Airflow developers serve?
Our Airflow developers work across fintech (transaction pipelines, regulatory reporting), healthcare (HIPAA-compliant data flows), e-commerce (inventory and analytics pipelines), SaaS (product analytics, usage metering), and media (content recommendation pipelines).
Do your developers integrate Airflow with dbt?
Yes. Airflow + dbt is a common pattern our developers implement. They set up dbt Core or dbt Cloud orchestration through Airflow DAGs, configure model dependencies, implement data quality checks with dbt tests, and build end-to-end ELT pipelines.
What Airflow executors do your developers work with?
Our developers are experienced with all Airflow executors: LocalExecutor for small deployments, CeleryExecutor for distributed task execution, KubernetesExecutor for dynamic pod-based scaling, and CeleryKubernetesExecutor for hybrid workloads. They select the right executor based on your scale and infrastructure.
Do you offer a trial period for Airflow developers?
Yes, we offer a 15-day risk-free trial for all dedicated engagements. If the developer doesn't meet your expectations within the first 15 days, we provide a replacement or full refund—no questions asked.
Can your team also handle Airflow infrastructure and monitoring?
Yes. Beyond DAG development, our engineers handle Airflow infrastructure: Kubernetes deployment with Helm, worker auto-scaling, Prometheus/Grafana monitoring for DAG performance, log aggregation, and alerting on task failures and SLA misses.
Ready to Hire Apache Airflow Developers?
Tell us about your data pipeline requirements and we'll match you with the right Airflow talent within 48 hours. 15-day risk-free trial included.
"We build relationships, not just technology."
-
Faster delivery
Reduce lead time and increase deploy frequency.
-
Reliability
Improve change success rate and MTTR.
-
Cost control
Kubernetes/GitOps patterns that scale efficiently.
No sales spam—just a short conversation to see if we can help.
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