(Senior) Data Engineer (f/m/x) für Berlin gesucht

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Job Kategorie: Gesundheits- und Sozialwesen Sozialwesen/Pflege

Stellenangebot Basisdaten

Arbeitsort:: DE 10963 Berlin
Umkreis:: keine Angabe.
Art der Arbeitsstelle:
Letze Aktualisierung:: 06.02.20262026-02-06

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Stellenausschreibung: (Senior) Data Engineer (f/m/x)

Arbeitgeber bzw. Arbeitsvermittler: audibene in Hamburg

Branche: Gesundheits- und Sozialwesen

Kategorie: Sozialwesen/Pflege

Stellenbeschreibung: Everyone should hear well to live well. This is what we believe in at audibene, driven by the purpose of changing lives of our customers. And we need your help in this exciting journey. About the role We're seeking an experienced Senior Data Engineer to help shape the future of hearing care through cutting edge data infrastructure. You'll take full ownership of the complete data lifecycle from ingestion and transformation to powering AI agents and LLMs through our semantic layer. This isn't traditional analytics; you're building data products that drive intelligent automation and decision making at scale. Your responsibilities Design and build robust, high performance data pipelines using our modern stack (Airflow, Snowflake, Pulsar, Kubernetes) that feed directly into our semantic layer and data catalog Create data products optimized for consumption by AI agents and LLMs where data quality, context, and semantic richness are crucial Structure and transform data to be inherently machine readable, with rich metadata and clear lineage that powers intelligent applications Take responsibility from raw data ingestion through to semantic modeling, ensuring data is not just accurate but contextually rich and agent ready Champion best practices in building LLM consumable data products, optimize for both human and machine consumers, and help evolve our dbt transformation layer Built data products for AI/LLM consumption, not just analytics dashboards Your profile 5+ years of hands on experience with complex ETL processes, data modeling, and large scale data systems Production experience with modern cloud data warehouses (Snowflake, BigQuery, Redshift) on AWS, GCP, or Azure Proficiency in building and optimizing data transformations and pipelines in python Experience with columnar storage, MPP databases, and distributed data processing architectures Ability to translate complex technical concepts for diverse audiences, from engineers to business stakeholders Experience with semantic layers, data catalogs, or metadata management systems Familiarity with modern analytical databases like Snowflake, BigQuery, ClickHouse, DuckDB, or similar systems Experience with streaming technologies like Kafka, Pulsar, Redpanda, or Kinesis What we offer At audibene, you'll make our customers happy every day by helping them hear better. You’ll work 4 days a week from our office (Berlin/Mainz) with a passionate team, and 1 day a week from home. As part of the audibene team, you’ll regularly join on- and offline team events, company off-sites, and the annual audibene Wandertag. We cover the cost of the Deutschland-Ticket so you can easily get wherever you need to go. Stay fit and healthy with access to over 50,000 gyms and wellness facilities through Urban Sports Club. We support your personal development with a wide range of programs, trainings, and coaching opportunities. Our office is dog-friendly, you're welcome to bring your furry friend to work! About audibene audibene/ hear.com is one of the fastest-growing health technology companies ever. Our unique digital business model has revolutionized the industry and the way hearing care is provided. Since we started our journey in Berlin in 2012, we have scaled up our team from 2 to over 1200 people in 8 international locations from Denver to Seoul. Driven by our belief that every person should hear well to live well, we have helped more than 200,000 customers to bring the joy of life back. Join us on our mission to transform the hearing care industry and change people’s lives!

Qualifikation: Arbeitskräfte

Verdienst:: n.a.

Bewerbung an: audibene
Am Strandkai 1
De 20457 Hamburg

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