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Data engineer (m|f|d)

München
MEAG
Data Engineer
Inserat online seit: Veröffentlicht vor 5 Std.
Beschreibung

Your tasks
* Flexibility: Mobile work (option to work from home a few days a week), 30 days of vacation
* Asset Accumulation & Retirement Planning: Company pension system & employee savings plan
* Development: Intensive professional & personal development (internal & external offerings), LinkedIn Learning access
* Health: Comprehensive company doctor services, Urban Sports cooperation
* Family: pme family service, childcare allowance, care assistance, cooperation with daycare centers, flexible working hours
* Other: Daily free lunch in our cafeteria, Free hot drinks & water, "Deutschland Ticket Job" subsidy, Events, Underground parking garage with e-charging infrastructure & much more!


*Please note that this list is based on current collective agreements. These may change. The list is for information purposes only. We do not accept any liability for individual points.


MEAG stands not only for a partnership-based relationship with customers, but also for fair treatment of applicants and employees. Regardless of gender. So if we use the masculine form of personal designations, this is purely for the sake of readability. Applicants with disabilities will be given preferential consideration if they are otherwise essentially equally qualified. Your profile
* Master’s degree in computer science or a related field
* Several years of experience with working with traditional AI or GenAI solutions
* 3+ years of working experience in data engineering
* Proficiency in data wrangling, data pipeline mgmt., and data quality frameworks/best practices
* Expertise in programming languages (e.g., Python, C++), query languages (e.g., SQL), and familiarity with big data tools (e.g., Apache Spark) and cloud platforms (e.g., Azure)
* Experience working with un-/structured data (ideally both) to ensure compatibility with model requirements, e.g.:
o Structured data: Experience in creating data models, -cubes, and relationship mapping between datasets
o Unstructured data: Skills in transforming data into vector embeddings and feature tables, proficiency in using tools for data annotation and metadata tagging (e.g., Dataloop AI, AWS SageMaker)
* Very good communication, collaboration, and stakeholder management skills
* Ability to work in a fast-paced environment, prioritize tasks, and meet deadlines
* Business proficiency in English (C1) and German (C1) are required.

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