Job
- Level
- Experienced
- Job Field
- Data, Back End
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Dusseldorf
- Working Model
- Hybrid, Onsite
Job Summary
In this role, you will develop scalable data pipelines and prepare structured and unstructured data for (Gen-)AI solutions, including MLOps execution and collaboration within agile teams.
Job Technologies
Your role in the team
- You are an important part of the (Gen-)AI implementation team, involved in strategic (Gen-)AI projects, and prepare large structured, semi-structured, and unstructured data sets to make them usable for (Gen-)AI solutions.
- You design and implement scalable data pipelines (batch/streaming) using modern technologies - e.g., Python, PySpark, SQL - and integrate data from various source systems - e.g., operational systems, databases, APIs, external data sources.
- You develop robust ETL/ELT pipelines, automate them using tools such as Kubernetes, Azure CosmosDB, Databricks, DLT /DBT, or similar, and ensure that data is available with quality assurance, versioning, and reproducibility.
- You participate in the deployment and operation of Machine Learning and (Gen)AI solutions (MLOps) with a focus on use cases based on structured, semi-structured, and unstructured data - including the integration of (Gen)AI applications and processes (e.g., MLFlow) - and advise operational units on utilizing the work results, especially in the initial and ongoing development of Machine Learning and (Gen)AI applications.
- You work closely with numerous stakeholders such as IT, business units, international locations, etc., in agile, interdisciplinary teams to jointly implement effective and productive (Gen)AI solutions.
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Our expectations of you
Education
- Completed university degree in Natural Sciences, (Applied) Mathematics, Computer Science, Business Informatics, or a related field.
Qualifications
- Willingness to innovate and proactive working methods, combined with the ability to think and act interconnectedly, to lay the foundation for the development and deployment of (Gen-)AI and LLM technologies.
- Preferably industry knowledge of the insurance sector, business-fluent proficiency in German (C1) and English (B2 / C1), as well as willingness to travel.
Experience
- Solid knowledge and experience in data modeling and visualization with a strong focus on scalable data management concepts - including experience with standardized ETL pipelines and data pipelines - as well as practical experience in deploying these, including MLOps.
- Solid knowledge in one or more programming, scripting, and database languages (e.g., Python, Spark, SQL) as well as experience with version control systems (GitHub) – including experience with cloud technologies (e.g., Azure, AWS).
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What we offer
- An exciting opportunity where you can apply your expertise.
- As you contribute to the successful development of ERGO, you can expect certain benefits from us as an employer, such as flexible working hours, development opportunities, fair compensation, and even free hot beverages and water.
- Mobile working is possible up to 50 percent of the monthly working hours and offers you a high degree of flexibility.
- We offer you the support you need to realize your full potential as well as to balance your work and private life appropriately.
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Benefits
Work-Life-Integration
Health, Fitness & Fun
Higher Take-Home Pay
Topics You Will Work On
Job Locations
About Your Employer
ERGO Group AG
ERGO is one of the leading insurance groups in Germany and Europe. The group is represented in around 30 countries worldwide and focuses on the regions of Europe and Asia. ERGO offers a comprehensive range of insurance, pension and service products. In its home market of Germany, ERGO is one of the leading providers across all lines of business.
Description
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Banking, Finance, Insurance
Data Engineer Digital Technologies / AI
- Location
- Dusseldorf
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
