Job
- Level
- Erfahren
- Job Feld
- Data, Back End
- Anstellung
- Vollzeit
- Vertragsart
- Unbefristetes Dienstverhältnis
- Ort
- München
- Arbeitsmodell
- Hybrid, Onsite
Job Zusammenfassung
In dieser Position entwickelst du robuste Datenpipelines mit Python und Spark, orchestrierst sie mit Apache Airflow und implementierst Infrastruktur as Code, um eine cloudbasierte Datenplattform zu optimieren.
Job Technologien
Deine Rolle im Team
- Design, Build and optimize batch and streaming data pipelines with strong performance, fault tolerance, and observability using Python, Spark, and Clickhouse.
- Develop and operate workflow orchestration with Apache Airflow to schedule, monitor, and manage data pipelines and transformations.
- Manage, model and document critical data systems for analytics using SQL and dbt to support business intelligence and reporting workloads.
- Implement infrastructure-as-code (e.g., Terraform) to provision and manage cloud-based data platform components.
- Containerize and deploy services using Docker and Kubernetes (and related tooling such as Helm).
- Collaborate with analysts, application teams and other stakeholders to turn requirements into technical designs and delivered solutions.
Unsere Erwartungen an dich
Qualifikationen
- Python - strong, idiomatic, tested. You write pipelines that other people can read and easily debug.
- SQL - advanced. Window functions, CTEs, query plans, and the instinct to know why a query got slow.
- Data modeling & warehousing - dimensional modeling, incremental vs. full-refresh strategies, slowly changing dimensions, and the trade-offs between them.
- dbt - building, testing, and documenting models in a real project.
- Apache Airflow - authoring DAGs, plus the operational side: backfills, retries, SLAs, and debugging a failed run.
- Docker & Kubernetes - you can containerize a job and understand what happens when a pod won't schedule.
- Git and CI/CD - branching, code review, and pipelines that gate merges.
- Knowledge of ClickHouse or another columnar OLAP engine (BigQuery, Redshift) table engines, partitioning, and MergeTree tuning are a big plus.
- Familiarity with infrastructure as code (IaC) - Terraform, Helm, Ansible.
- Working knowledge of Apache Spark - PySpark or Scala.
- Attention to detail - You care about correctness and you build the checks that prove it. In data engineering, a silently wrong number is worse than a loud failure.
- Ownership - you run what you build, and you improve it when needed.
- Clear communication - you can effectively explain in a pipeline to an analyst and a trade-off to a stakeholder.
- Pragmatism - you can tell the difference between the right long-term design and the short-term solution, and you know when each one applies.
- Collaboration - you work well with data engineers, analysts, and other product and backend teams.
- English - fluent, written and spoken.
Erfahrung
- 4+ years building and running production data pipelines.
- AWS - hands-on experience with S3 and the surrounding data services (Athena, Kinesis, EKS, Lambda).
- Good experience with streaming data ingestion technologies such as Kafka, Kinesis, or similar.
- Experience with data lake architectures - Parquet, Iceberg, or Delta Lake, and an understanding of layered lake design (bronze silver gold).
- Experience with BI tooling - Apache Superset, Looker, Tableau, or equivalent.
- Strong experience integrating third-party APIs - handling inconsistent schemas, rate limits, and unpredictable failure modes at scale.
Unser Angebot
- A culture that values personal and professional development, with internal mobility opportunities.
- A supportive and open-minded team that embraces diverse perspectives and innovative ideas.
- 32 days of paid vacation plus your birthday off, giving you the time you need to recharge.
- A flexible hybrid working scheme to balance work and life.
- Access to a learning budget and internal training to help you grow in your role.
- Mental health coaching to support your well-being.
- Regular global and local get-togethers to celebrate successes and build connections.
- The possibility of taking a sabbatical after three years with the company.
- A cloud-based company setup, providing flexibility and collaboration opportunities no matter where you are.
Themen mit denen du dich im Job beschäftigst
Job Standorte
Das ist dein Arbeitgeber
Atolls
Atolls GmbH ist die größte Plattform für Shopping-Engagement in Europa und beschäftigt über 1.000 Mitarbeiter in mehr als 20 Märkten. Das Unternehmen bringt Verbraucher mit Marken und Händlern zusammen, um intelligente Kaufentscheidungen zu fördern. Zu den bekannten Plattformen zählen mydealz.de, Shoop und Coupons.com.
Description
- Unternehmenstyp
- Etablierte Firma
- Arbeitsmodell
- Hybrid, Onsite
- Branche
- Internet, IT, Telekom