Position Summary:

SparkCognition’s Renewable Suite is the world's leading AI enabled SaaS platform that provides asset performance management and prescriptive analytics software to ever growing renewable energy power plants by combining the power of machine learning, big data, and deep domain expertise. Our platform works across multiple asset types such as wind, solar, storage and DC coupled assets to offer insights to our customers across their fleets. As a Data Platform Engineer you will be working closely with team members across domains with deep technical skills and passion for clean energy.

Join us in:

• Bringing large volumes of data from wind, solar, storage sites to cloud
• Architecting scalable data ETL and MLOps pipelines and workflows 
• Work closely with delivery engineering team for successful hand-off of with detailed documentation of ETL and workflow 

You’ll have:

• Excellent programming skills in Python are mandatory, along with deep expertise in relational databases (MSSQL/MySQL/Postgres)
• 3+ years of hands-on experience in data engineering, with a solid foundation in data engineering architecture principles
• Experience with platforms such as Ignition, Kepware, OSIsoft/AVEVA PI
• Strong understanding of serverless architectures and experience building scalable ETL pipelines 
• Effective communicator and leader, capable of initiating and driving projects

It would be great if you had: 

• Experience in renewable energy or IoT time series data
• Experience in workflow orchestration technologies like Airflow or Prefect
• Experience working with cloud-native tools, particularly AWS or GCP
• Hands-on experience in DevOps, with a focus on cloud-native technologies