Battery Data Engineer

What does a Battery Data Engineer do at Fluence?

• Data Pipeline Development: Design, develop, and maintain data pipelines to collect and process large volumes of battery performance and health data from various sources. 
• Data Integration: Integrate data from multiple sources, ensuring data consistency, quality, and reliability. 
• Data Storage and Management: Implement and manage data storage solutions, ensuring efficient data retrieval and storage. 
• Data Processing and Analysis: Develop and optimize algorithms for processing and analyzing battery data to derive meaningful insights and support product development. 
• Collaboration: Work closely with data scientists, engineers, and product managers to understand data requirements and deliver data solutions that meet business needs. 
• Performance Monitoring: Monitor the performance of data systems and make improvements as needed to ensure data accuracy and system reliability. 
• Documentation: Document data architectures, pipelines, and processes to ensure transparency and knowledge sharing within the team. 
• Technical Leadership: Provide guidance and mentorship to junior data engineers, fostering a collaborative and innovative team environment. 

What does the ideal candidate look like?

• Education: Bachelor’s degree in computer science, Data Engineering, Electrical Engineering, or a related field. Advanced degree preferred. 
• Experience: Minimum of 3 years of experience in data engineering, preferably within the battery or energy storage industry. 
• Technical Skills: 
• Proficiency in data engineering tools and technologies (e.g., SQL, Python, Apache Spark, Kafka). 
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and data storage solutions (e.g., SQL/NoSQL databases, data lakes). 
• Knowledge of data integration and ETL (Extract, Transform, Load) processes. 
• Familiarity with big data processing frameworks and tools. 
• Experience with MLOps techniques and practices. 
• Proficiency in data visualization tools (e.g., Tableau, Power BI). 
• Experience with version control and DevOps practices (e.g., GitHub, GitLab). 
• Analytical Skills: Strong analytical and problem-solving skills with the ability to interpret complex data and provide actionable insights. 
• Communication Skills: Excellent verbal and written communication skills with the ability to collaborate effectively with cross-functional teams. 
• Attention to Detail: High level of accuracy and attention to detail in data processing and analysis. 
• Additional Skills and Experience: 
• Battery Technology: Knowledge of battery technology and energy storage systems is a plus. 
• Machine Learning: Experience with machine learning and data science methodologies is an advantage. 
• Agile Methodologies: Familiarity with agile methodologies and project management tools (e.g., Jira).