Job Description

Job Summary:
The Data Engineer will manage and analyze the company's data from battery systems, microgrids, and energy management solutions. This role includes designing databases, developing analytics/reporting systems, and applying machine learning (ML) for actionable insights. The Data Engineer will also integrate AI/ML into the EMS product to drive innovation in energy management.
Key Responsibilities:

• Design and maintain robust database architectures to support operational data from battery systems and microgrids.
• Develop and optimize data pipelines to ensure seamless ingestion, processing, and storage of structured and unstructured data.
• Ensure data integrity, security, and availability through best practices in database management.
• Develop and implement data analytics and visualization tools to provide insights into system performance.
• Create automated reporting solutions to track key metrics, enabling data-driven decision-making across the organization.
• Work closely with stakeholders to understand reporting needs and deliver actionable insights through dashboards and custom reports.
• Analyse historical data to identify patterns, trends, and correlations in battery system and microgrid performance using statistical methods and AI tools.
• Develop trend forecasting models to anticipate system behavior and provide proactive recommendations for system optimization.
• Find innovative ways to optimize energy costs and management.
• Lead initiatives to integrate AI and machine learning models within the EMS product, focusing on predictive analytics and anomaly detection.
• Collaborate with software developers to create data-driven features that enhance the EMS products capabilities and user experience.
• Identify opportunities for innovative new services based on data trends and lead their development.
• Collaborate with the EMS team, software engineers, and product owners to align data initiatives with product objectives.
• Facilitate training and workshops to promote AI and ML technologies across the company, ensuring teams understand and utilize data-driven insights.

• Bachelors degree in Computer Science, Data Science, Engineering, or a related field.
• Minimum of 3-5 years of experience in data engineering, analytics, or a related role.
• Proven experience in designing and managing databases, developing ETL pipelines, and building analytics solutions.
• Hands-on experience with AI/ML technologies and frameworks, such as TensorFlow, Scikit-Learn, or similar.
• Proficiency in SQL, Python, and data visualization tools (e.g., Power BI, Tableau), including Python Data Analysis libraries
• Experience with cloud platforms for data storage and processing (e.g., AWS, Azure).
• Strong understanding of data warehousing concepts, data modeling, and big data technologies (e.g., Spark, Hadoop).
• Strong understanding of time series data analysis, pattern recognition, forecasting and model building and using AI tools to achieve these.