Job
- Level
- Senior
- Location
- Munich
- Working Model
- Hybrid, Onsite
- Job Field
- Data, Back End
- Employment Type
- Full Time
- Contract Type
- Permanent employment
Job Summary
In this role, you will develop data pipelines, design and maintain Airflow DAGs and dbt pipelines, manage Kubernetes environments, and collaborate with the SRE team to optimize infrastructure and deployments.
Job Technologies
Your role in the team
- As a Senior Data Ops Engineer, you will drive the reliability, scalability, and performance of our data platform.
- You will shape how we manage data pipelines, infrastructure, and tooling.
- You will embed automation, strengthen observability, and ensure our data infrastructure meets the Insights team's needs.
- Your impact will extend beyond individual pipelines, influencing processes, teams, and the long-term stability of our data platform.
- You will design, build, and maintain Airflow DAGs, data ingestion pipelines, and dbt pipelines that move and transform data across our platform.
- You will maintain our Kubernetes namespaces and Trino and Airflow clusters and manage multiple environments end-to-end.
- You will coordinate closely with the SRE team on infrastructure and deployment topics, and work hand in hand with the Backend team to align on shared architecture decisions.
- You will expand our monitoring and alerting setup, prepare internal metrics that give teams clear visibility into system health, and assist with user-reported bugs as they come in.
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Our expectations of you
Qualifications
- Strong prioritization skills and a practical approach to changing priorities.
- Excellent English communication skills.
- A good understanding of networking, which helps you troubleshoot connectivity issues across our infrastructure.
Experience
- Strong SQL skills, paired with experience in data transformation tools such as dbt, SQLMesh, or similar.
- Solid experience with the Linux command line.
- Hands-on experience with Kubernetes, Helm charts, Docker, and similar containerization tooling.
- Experience with database management, ideally with PostgreSQL and MySQL.
- Starke Erfahrung mit CI/CD-Pipelines und Git.
- Experience working with AI, including writing skills or tools for AI systems.
- Solid experience with Python development - or, alternatively, another object-oriented programming language.
- You bring 4+ years of experience in data operations, data engineering, or data platform operations, including building and maintaining data pipelines and supporting production data infrastructure.
- Experience with Apache Spark or Trino SQL for large-scale data processing.
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What we offer
- A trusting environment and lifelong learning for your individual development.
- Set personal development goals, receive support and regular feedback.
- Take responsibility for a variety of tasks, find out what you like to work on, and find your way to make your own personal impact with us!
- Regular team events, parties, and a talented international team with a common goal that unites us all.
- We offer flexibility through our hybrid working model, conveniently arrange your working hours, and the ability to work from abroad within the EU.
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Benefits
Health, Fitness & Fun
Topics You Will Work On
Job Locations
About Your Employer
EQS Group AG
Die EQS Group ist ein internationaler Anbieter von regulatorischen Technologien (RegTech) in den Bereichen Corporate Compliance und Investor Relations. Mehrere tausend Unternehmen weltweit schaffen mit der EQS Group Vertrauen, indem sie komplexe Compliance-Anforderungen erfüllen, Risiken minimieren und transparent mit Stakeholdern kommunizieren. Die Produkte der EQS Group sind in der cloud-basierten Software "EQS COCKPIT" gebündelt. Damit lassen sich Compliance-Workflows in den Bereichen Hinweisgeberschutz und Case Management, Richtlinien-Management, Insiderlistenverwaltung und Meldepflichten professionell steuern.
Description
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Internet, IT, Telecommunication
Senior Data Ops Engineer
- Location
- Munich
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
- English Only
- English only required
