Data Engineer AI (m/f/d)

Rohde & Schwarz; Dresden; On-site; EUR 70,000 - 100,000; Full time

Job summary

Rohde & Schwarz in Dresden is seeking a data engineer to design and implement scalable data pipelines supporting ingestion, ETL/ELT, and batch and streaming use cases. You will develop data models, schemas, catalogs, and feature stores to enable reliable data access across product systems.

You will ensure data quality, lineage, and observability for high‑performance real‑time sources, and integrate diverse storage solutions.

Responsibilities

• You design and implement scalable data pipelines for ingestion, ETL/ELT, as well as batch and streaming use cases.
• You develop and maintain data models, schemas, catalogs, and feature stores for reliable and discoverable data access.
• You ensure data quality, validation, lineage, and observability for high-performance real-time sources.
• You integrate and operate storage solutions such as object stores, SQL/NoSQL and vector databases, and optimize access patterns for product systems.
• You ensure reproducibility and metadata tracking in ML workflows through experiment and feature lineage tracking.
• You automate CI/CD, monitoring, alerting, and capacity planning for pipelines, thereby ensuring operational reliability.

Job description

Introduction

You build the data pipelines that AI systems for a safe, connected world are built on.

Tasks

• You design and implement scalable data pipelines for ingestion, ETL/ELT, as well as batch and streaming use cases.
• You develop and maintain data models, schemas, catalogs, and feature stores for reliable and discoverable data access.
• You ensure data quality, validation, lineage, and observability for high-performance real-time sources.
• You integrate and operate storage solutions such as object stores, SQL/NoSQL and vector databases, and optimize access patterns for product systems.
• You ensure reproducibility and metadata tracking in ML workflows through experiment and feature lineage tracking.
• You automate CI/CD, monitoring, alerting, and capacity planning for pipelines, thereby ensuring operational reliability.