Data Infrastructure Engineer

Doodle; Berlin; Vor Ort; EUR 70.000 - 110.000; Vollzeit

Zusammenfassung

Doodle is seeking a Data Infrastructure Engineer in Berlin to design, build and operate scalable data platforms that power data-driven decisions across teams. You will collaborate with SRE, product, engineering and analytics to make data reliable, secure and easy to use.

You will work on streaming and batch workflows (Kafka, Airflow), optimize Redshift performance, and implement infrastructure as code with a security-first mindset across cloud environments.

Qualifikationen

• 2+ years in data platform engineering or scalable software systems.
• Clear communication with technical and non-technical stakeholders.
• Cloud and DevOps: CI/CD, infrastructure as code and Kubernetes.
• Kafka and Avro: schema design, serialization and evolution.
• Reliability and security: observability, incident response and root-cause analysis.

Aufgaben

• Design, build and operate scalable data infrastructure for ingestion, transformation, storage and serving.
• Run streaming pipelines with Kafka and Avro; manage batch workflows with Airflow.
• Keep Redshift performant, well-modeled and cost-effective.
• Manage secure, reproducible cloud environments with infrastructure as code.
• Own SLOs, runbooks, and alerts for critical data systems.
• Improve discoverability through data cataloging, lineage and self-service tooling.

Kenntnisse

Kafka

Airflow

Redshift

Kubernetes

CI/CD

Infrastructure as Code

Data modeling

Communication skills

Security awareness

Tools

Dbt

Jobbeschreibung

• Doodle is a B2B SaaS platform used by millions of professionals to coordinate meetings and collaborate across teams and companies
• We're building the future of scheduling and productivity, working on hard problems where human collaboration meets digital efficiency
• We craft elegant solutions to complex problems, and we're looking for passionate problem solvers who share that drive
• Our product, engineering and analytics teams rely on data every day to decide what we build next
• As our Data Infrastructure Engineer, you'll bring data engineering and infrastructure together, designing, building and running the platforms that keep our data reliable, secure and easy to use
• You'll work closely with our SRE, product, engineering, analytics and security teams to make data simpler for everyone
• Build the platform: design, build and operate scalable infrastructure for data ingestion, transformation, storage and serving. Run streaming flows with Kafka and Avro, orchestrate batch workflows in Airflow, and keep Redshift performant, well-modeled and cost-effective
• Run infrastructure as code: manage secure, reproducible cloud environments for development, testing and production, with sensible cost controls
• Keep it reliable and secure: own SLOs, runbooks and alerts for critical data systems. Protect sensitive data through access controls, encryption, secrets management and retention policies
• Fix problems at the root: investigate incidents, lead root-cause analysis and implement preventative improvements
• Make data easy to use: improve discoverability through cataloging, lineage, ownership and quality testing, and build documentation, tooling and self-service workflows so analytics and engineering teams can work independently

• Reliability and security: observability, incident response and debugging pipeline failures, with a security-conscious approach to data access, privacy and secrets
• Dbt: experience with it is a plus
• Clear communication with both technical and non-technical stakeholders
• Cloud and DevOps: CI/CD, infrastructure as code and Kubernetes, plus data lakes and open table formats
• Kafka and Avro: schema design, serialization and evolution
• Redshift and production Airflow: data modeling and performance tuning
• 2+ years in data platform engineering or scalable software systems