Additionalinformation

Additional Information

What we offer you:

Challenges in an international environment | career opportunities in one of the best companies in the world | flexible hours | medical services | discounts for employees | sports and health related activities | canteen | good access to public transports | space for creativity.

Success stories don´t just happen. They are made...

Make it happen! We are looking forward to your application!

Companydescription

Company Description

Welcome to Bosch

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference.

With over 300 specialized associates and around 15 nationalities, Bosch activities in Lisbon are focusing on sales, marketing, communication, training, nearshoring services and shared support for human resources services to Europe. The diversity, commitment and know-how of the team are the key success factors of this organization.

Bosch Service Solutions develops and delivers Customer Experience, Mobility and Monitoring solutions for companies and their customers.

Our teams find fast and efficient solutions for thousands of people on a daily basis – from claim management to life-saving emergency calls, among other services. Define the standards and become a pioneer together with around 9000 associates worldwide.

Jobdescription

Job Description

Platform & Pipeline Engineering

• Develop, automate, and maintain resilient data pipelines connecting on-premises
• laboratory equipment, high throughput test benches, and edge systems to Microsoft Azure.
• Investigate, unpack, and parse complex, non-standard, binary, proprietary, and undocumented file formats where standard connectors do not exist.
• Implement parsers and normalization routines capable of ingesting diverse technical data streams, for example:

1. High-frequency sensor streams, time series, and bus telemetry.
2. Multi-dimensional scientific arrays, spatial grids, and spectral data.
3. - Hierarchical, nested, and unstructured binary logs or custom ASCII exports.
4. Event logs, operational metadata, and intermittent experimental batch runs.

• Clean, validate, and transform fragmented or schema-less raw data into optimized, partitioned Lakehouse tables (Delta Lake/Parquet) ready for analytics and ML model training.
• Deploy, monitor, and maintain pipeline resources on Azure using Terraform, Databricks, and containerized workflows following established team templates.

Collaboration & Lab Support

• Work directly alongside experimental scientists, lab engineers, and technicians to decipher raw measurement files, clarify domain-specific semantics, and automate recurring data uploads.
• Collaborate closely with solution architects and senior engineers to implement data ingestion patterns, cataloguing schemas, and governance standards.
• Maintain clear technical documentation, code comments, and onboarding walkthroughs to help research teams connect their equipment seamlessly.
• Support proof-of-concept initiatives exploring metadata integration with corporate AI assistants, data discovery catalogs, and modern data tools.

Qualifications

Education

• BSc, MSc or Ph.D. in Data Engineering, Computer Science, Software Engineering, Applied Physics, Electrical Engineering, or a related field.

Experience

• 3+ years of professional experience in data engineering, building automated and reliable data pipelines.
• 1–2 years of practical experience handling heterogeneous, non-standard, or binary data sources (e.g., physical sensor logs, laboratory exports, hardware telemetry, or raw byte streams).
• 1+ years of hands-on experience utilizing Apache Spark (preferably Databricks) and Microsoft Azure in production environments.
• Demonstrated experience deciphering, parsing, or converting non-standard, legacy, or custom data formats into structured data structures.

Technical Skills

• Strong proficiency in Python for data manipulation (including binary data handling using modules like struct, byte manipulation, NumPy, Pandas, and PySpark) and Bash.
• Solid understanding of modern Lakehouse concepts (Delta Lake), distributed data processing, SQL, and NoSQL/document datastores.
• Proficient with Git, GNU/Linux environments, and working knowledge of Infrastructure as Code (Terraform).
• Practical experience with standard transport mechanisms (e.g., REST APIs, SFTP, Kafka/Event Hubs, or IoT/streaming protocols).

Mindset & Soft Skills

• Strong analytical mindset with a natural curiosity to open unfamiliar files, inspect headers, and solve data decoding puzzles.
• Friendly, empathetic communication style with the ability to bridge conversations between laboratory technicians, domain scientists, and software teams.
• C2 CEFR level in English, written and spoken.

Nice to Have

• Experience with scientific/hierarchical file formats (e.g., HDF5, NetCDF, Parquet, Protobuf).
• Familiarity with industrial telemetry or time-series historian protocols (e.g., OPC UA, MQTT).
• Exposure to Azure analytics tooling (Azure Data Factory, Azure Event Hubs, Azure Data Explorer).
• Experience with vectorial databases.

Languages

• Fluent in Portuguese.
• B2 CEFR level in English, written and spoken.
• B2 CEFR level in German, written and spoken is a plus