Senior Data & Backend Software Engineer (f/m/d)

Mission Brief 

Join us in building the systems and software that empowers our engineering and operation departments to analyze flight data and make data-driven decisions. As a Data & Backend Software Engineer, you will help transform large volumes of structured and unstructured data into reliable, accessible, and actionable information. Your work will enable data-driven decision-making across the company and unlock insights that drive innovation and operational excellence. 

Your Role in Our Space Mission: 

As part of our Data and Analytics team, you will design, develop, and operate the systems that ingest, process, store, and serve data at scale. 

You will: 

• Build modern, scalable, and high-performance solutions for our engineering and operation platform. 

• Strong understanding and at least 6 years of hands-on experience in one of the following languages: C#, Java, Rust, Python.   

• Define data ingestion, processing, storage, and access patterns to ensure reliability, scalability, and maintainability. 

• Develop data services, APIs, pipelines, and data products that make data available to engineers, analysts, and business stakeholders. 

• Design and implement robust ETL/ELT processes to ingest and transform data from a wide variety of sources. 

• Contribute to data architecture, modeling, and storage decisions to ensure consistency, availability, low latency, and long-term sustainability of the platform. 

• Ensure data quality and integrity through validation processes, monitoring, and adherence to data governance principles. 

• Provide observability and monitoring of platform components, enabling rapid detection and resolution of issues. 

• Author and maintain architectural documentation, technical specifications, and user-facing documentation. 

• Collaborate with cross-functional teams to understand data needs and deliver impactful solutions. 

• Guide less experienced engineers by sharing your knowledge and know-how, promoting engineering best practices and continuous learning. 

Qualification Checklist  

• A degree in software engineering, computer science, data science or similar  

• Strong experience with batch and streaming data processing 

• Good understanding of time-series data concepts, including sampling rates, decimation, signal integrity, and frequency-domain analysis 

• Practical experience in optimizing and efficient implementation of native data processing and DataFrame-based processing 

• Excellent skills in querying, transforming, and optimizing large-scale datasets 

• Solid understanding of modern data architectures, including Lakehouse, Data Warehouse, and Medallion Architecture patterns 

• Hands-on experience with analytical storage technologies such as Delta Lake and Apache Iceberg 

• Experience with Apache Kafka and event-driven architectures 

• Experience with modern data platforms such as Microsoft Fabric, Azure Data Factory, Databricks, or Snowflake 

• Strong understanding of software engineering principles, including maintainability, testing, and automation 

• Understanding of cloud infrastructure, networking concepts, and platform operations 

• Experience with Protobuf encoding and columnar file formats (Parquet, Arrow, Zarr, Arrow Flight) 

• Experience with observability, monitoring, and telemetry solutions 

• Experience with OLAP databases and/or TSDBs (like ClickHouse, Apache Druid, InfluxDB)