Senior Python Developer

Project description:

In the context of developing a modular control center system (MCCS) Home, the data teams provide systems and solutions to handle and provide master data as well as real time data from our electrical grid.
The provided products of the product line include generic services and specific data products that are used by services in other modules and are enabler for user facing products like monitoring or control. Further, the whole product cluster uses a CIM-based data modeling approach and the data teams supports other teams to provide services in the product cluster in a data mesh like architecture.

Duration 01.11.2024 – 30.12.2025 (The end of the project is in 2027)
Location: Remote 95%, Trips to Berlin (paid by client)

Requirements:

•  Degree in Computer Science, Information Technology, or a related field.
• Advanced knowledge of Python and Software Engineering Principles (min 5 Years).
• Strong familiarity with REST API backend development.
• Experience with Docker, HELM, Kubernetes, and microservices architecture.
• Experience with software security patterns and relevant protocols (oAuth / openid).
• Experience with Data tools & frameworks (Kafka, Relational Databases, stream processing etc.).
• Experience with YAML configuration files, Protobuf Serialization.
• Experience with cloud platforms like AWS, Google Cloud, or Azure is a plus.
• Experience with data catalogue tools, data mesh architectures, and federated software architectures is a plus.
• Knowledge of and experience with ETL frameworks is a plus.
• Experience in good documentation practices for software systems.
• Strong communication skills.

Responsibilities:

• The Contractor designs and develops REST-based and Kafka-based APIs for Master Data Access and integration with other systems with a focus on security.
• The Contractor optimizes data storage and retrieval systems for performance and efficiency.
• The Contractor ensures the scalability and reliability of the data infrastructure.
• The Contractor optimizes data storage and retrieval systems for performance and efficiency.
• Project related collaboration with data scientists, data architects and other data engineers to ensure data accuracy and consistent data delivery especially related to data governance decisions.
• Identify, design, and implement internal process improvements, including automating manual processes, optimizing data delivery, and re-designing infrastructure for greater scalability.
• Project related work with stakeholders to consult with data-related technical issues and consult their data infrastructure needs. Evolve the data platform to fit the needs of stakeholders.
• Build data expertise and take responsibility for data quality for the pipelines you build.