Associate Engineer

Enphase Energy is a global energy technology company and a leading provider of solar, battery, and electric vehicle charging products. Founded in 2006, our innovative microinverter technology revolutionized solar power, making it a safer, more reliable, and scalable energy source. Today, the Enphase Energy System enables users to make, use, save, and sell their own power. Enphase is also one of the most successful and innovative clean energy companies in the world, with more than 80 million products shipped across 160 countries.   Join our dynamic teams designing and developing next-gen energy technologies and help drive a sustainable future!About the RoleThe Software Engineer role will be responsible for Supporting Enphase Analytics and Data-warehouse team. Provides support for the data management/Governance activities of the organization. Collaborates with Engineering/Quality/CS teams/Factory and various other teams. What you will be doing

•  Design, develop, and maintain Analytics/dashboards/Automation and reports
•  Work closely with stakeholders to understand their needs and translate them into business/DW solutions
•  Ensure the performance optimization, quality, and responsiveness of the dashboards
•  Collaborate with the team to define, design, and ship new features
•  Identify and correct bottlenecks and fix bugs
•  Help maintain code quality, organization, and automatization

 Essential duties/responsibilities

• Strong understanding of Datawarehouse Concepts
• Experience translating theoretical concepts into engineered features, with a demonstrated ability to create features capturing important events or transitions within the data
• Expertise in crafting custom features that highlight unique patterns specific to the dataset or problem, enhancing model predictive power. Ability to combine and synthesize information from multiple data sources to develop more informative features
• Advanced knowledge in Apache Spark (PySpark, SparkSQL, SparkR) and distributed computing, demonstrated through efficient processing and analysis of large-scale datasets. Proficiency in Python, R, and SQL, with a proven track record of writing optimized and efficient Spark code for data processing and model training
• Hands-on experience with cloud-based machine learning platforms such as AWS SageMaker and Databricks, showcasing scalable model development and deployment
• Demonstrated capability to develop and implement custom statistical algorithms
• Proficiency in statistical methods for identifying patterns and trends in large datasets, essential for predictive maintenance
• Experience optimizing code for performance in high-throughput, low-latency environments. Experience deploying models into production, with expertise in monitoring their performance and integrating them with CI/CD pipelines using AWS, Docker, or Kubernetes
• Familiarity with end-to-end analytical architectures, including data lakes, data warehouses, and real-time processing systems
• Experience creating insightful dashboards and reports using tools such as Power BI, Tableau, Incorta or custom visualisation frameworks to effectively communicate model results to stakeholders