Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions.
We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.
In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing.
About project:
We are looking for Data Engineers with strong Apache Airflow experience to join a project focused on customer enablement and engineering for a managed Airflow platform. The project supports data engineering teams in adopting, integrating, and operating Apache Airflow within their existing technology ecosystems.
This role is a great opportunity to combine hands-on Airflow engineering with technical consulting and customer enablement. You will help customers design and troubleshoot DAGs, integrate Airflow with their data platforms, and successfully transition workloads into stable production environments.
You will work closely with customer data engineering teams and an internal project owner, providing technical guidance while helping customers adopt best practices and resolve complex platform and production challenges.
You will:
- provide hands-on support with Apache Airflow configuration, DAG development, scheduling, and troubleshooting,
- advise customer data engineering teams on best practices for using Airflow across different technology stacks,
- help customers integrate Airflow with their existing data ecosystems, including cloud data warehouses, transformation tools, and Infrastructure as Code solutions,
- support customers during initial platform adoption and production onboarding,
- troubleshoot complex Airflow and distributed system issues and guide customers towards stable and reliable solutions,
- assist customers with operational challenges related to scheduling, dependencies, failures, and production workloads,
- deliver technical guidance, enablement, and knowledge sharing to customer engineering teams,
- collaborate with the internal project owner on scope, status tracking, priorities, and delivery activities,
- contribute to documentation and reusable technical guidance for common Airflow use cases and issues,
- work independently in a remote and distributed environment,
Your profile:
- strong hands-on experience with Apache Airflow, including DAG development, scheduling, dependencies, and operational concepts,
- professional experience with Python,
- commercial experience working with data engineering platforms or data infrastructure,
- experience in a customer-facing, consulting, advisory, support, or technical enablement role,
- strong troubleshooting skills with distributed systems and production environments,
- ability to understand complex technical issues and translate them into practical solutions,
- strong communication and customer empathy, particularly when providing technical training and support,
- ability to work independently and take ownership of technical issues,
- experience working effectively in remote and distributed international teams,
- practical understanding of Kubernetes and containerized environments,
- experience working with managed cloud services,
- familiarity with at least one modern data technology stack such as Snowflake, dbt, or Terraform,
- experience delivering technical workshops, training sessions, or customer enablement activities,
- ability to quickly learn new platforms, technologies, and internal tooling,
Nice to have:
- experience administering Apache Airflow in production environments,
- experience with Infrastructure as Code technologies such as Terraform,
- familiarity with SQL and analytical data workflows,
- previous experience in customer support, Site Reliability Engineering, or platform engineering roles,
- experience working with enterprise customers during onboarding, migration, or platform adoption phases,
- experience integrating Airflow with cloud data warehouses, transformation platforms, or other modern data engineering tools,
Recruitment Process:
CV review – HR call – Interview – Client Interview – Decision
