Battery Data Engineer

6 Months ago • 5 Years + • Data Analyst

Job Summary

Job Description

Fluence is hiring a Senior Battery Data Engineer to develop, implement, and optimize data pipelines for battery performance and health data. Must have strong experience in data engineering tools & technologies like SQL, Python, Apache Spark, Kafka and cloud platforms (AWS, Azure, Google Cloud) and data storage solutions.
Must have:
  • Data Engineering
  • Cloud Platforms
  • Data Storage
  • Battery Data
Good to have:
  • Machine Learning
  • MLOps Techniques
  • Agile Methodologies
  • Battery Technology

Job Details

Senior Battery Data Engineer 

Company Overview: Fluence is a leader in energy storage solutions, committed to innovation and excellence in battery technology. We are dedicated to advancing the integration of renewable energy and ensuring the reliability and efficiency of energy storage systems. Join our team and contribute to a sustainable future. 
 
Position Overview: We are seeking a highly skilled and experienced Senior Battery Data Engineer to join our Battery Systems Engineering team. The Senior Battery Data Engineer will be responsible for developing, implementing, and optimizing data pipelines and architectures to collect, process, and analyze battery performance and health data. This role will provide technical leadership and work closely with cross-functional teams to support data-driven decision-making and enhance our battery intelligence solutions. 

Key Responsibilities: 

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. 

Qualifications: 

Education: Bachelor’s degree in computer science, Data Engineering, Electrical Engineering, or a related field. Advanced degree preferred. 

Experience: Minimum of 5 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). 
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