disruptive innovation is a
team effort

What you’ll be doing

• Analyze, develop and maintain data in close cooperation with our Data Science team
• Create efficient data pipelines for machine learning models
• Help set up a data lake and ETL pipeline to handle data management
• Improve data quality and efficiency
• Continuously monitor and visualize data
• Act as the company’s database administrator ensuring state-of-the-art database management

What you need to bring

• Bachelor's degree in Computer Science or a related technical field. Master’s degree or higher is preferred
• Extensive experience working with Python and SQL
• Hands-on experience working with PostgreSQL, TimescaleDB and AWS S3
• A detailed understanding of ETL and data virtualization
• Comfortable with frameworks such as PySpark and Dask
• Applied experience with managing databases on the cloud
• Experience with data lakes, AWS, Airflow/Dagster is a plus

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What you’ll be doing

• Suggest improvements to deployment tools, systems and processes
• Write programs in Go/Python, and shell scripts to simplify deployment operations
• Evaluate various AWS services for suitability in our infrastructure
• Help make technical architecture and design decisions
• Monitor various components of our infrastructure from a high-level
• Help set up dashboards for other teams to perform lower-level monitoring
• Educate other team members in best DevOps practices
• Help us transform completely to maintaining our infrastructure as code

What you need to bring

• Bachelor's degree in Computer Science or a related technical field. Master’s degree or higher is preferred
• Experience with Go, Python and shell scripting
• Hands-on experience working with APIs (REST preferred)
• Comfortable with IaC tools such as terraform, pulumi or cloudformation
• A detailed understanding of cloud technologies and containerization tools such as docker
• Comfortable with SQL/NoSQL databases such as PostgreSQL/redis and monitoring tools like Grafana
• Experience with AirFlow/dagster and similar data pipeline tools is a plus
• Applied experience with version control systems such as git
• Ability and willingness to work independently, and across various backend tasks

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What you’ll be doing

• Analyze and model large amounts of fundamental and technical data and derive insights to maximize returns on energy trading
• Continuously apply state-of-the art machine learning techniques and frameworks to large and multivariate data (historic and real-time)
• Develop scalable code/queries and end-to-end pipelines to deploy machine learning models on production
• Work closely with resonanz Backend and Product Management teams to ensure system efficiency and business logic at all times

What you need to bring

• Bachelor's degree in Computer Science, Mathematics, Physics, or a related technical field. Master’s degree or higher is preferred
• A detailed understanding of Python, Pandas, Numpy, Scikit-learn, Keras/Tensorflow, and other data science frameworks
• Basic knowledge of Python-based visualization libraries (e.g. Dash, Bokeh, or similar)
• Applied experience with developing machine learning applications to solve real-world problems 
• Comfortable with mathematical concepts behind machine learning 
• Hands-on experience with database queries and handling big amounts of data
• Ability and willingness to work independently 
• Reinforcement learning and risk estimation skills are a bonus

What you’ll be doing

• Help make database architecture and design decisions
• Develop PL/pgSQL scripts to speed up and automate common tasks
• Implement tracking of all database changes as code
• Set up roles, permissions and processes for accessing and working with the data
• Automate provisioning of the databases in our AWS cloud
• Review SQL queries written by other team members and give feedback
• Monitor and improve database performance

What you need to bring

• Bachelor's degree in Computer Science or a related technical field. Master’s degree or higher is preferred
• Extensive experience working with both relational databases (PostgreSQL preferred) and non-relational databases (Redis preferred) Knowledge of timeseries databases is a plus
• Detailed understanding of database version control systems (Liquibase preferred)
• Hands-on experience working with multivariate data sets.
• A good understanding of cloud technologies, particularly those dealing with cloud storage solutions
• Comfortable interfacing with monitoring tools like Grafana
• Applied experience with version control systems such as git
• Ability and willingness to work independently