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 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 on engineering projects to design, construct, install, test and maintain highly scalable data management systems

You’ll have:

• Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. 
• Experience with Python
• 2+ years of experience building and optimizing ‘big data’ data pipelines, architectures 
  and data sets. Startup experience a plus
• Experience building ETL pipelines from large disconnected datasets. 
• Experience with big data tools: Hadoop, Spark, Kafka, etc. 
• Experience with relational databases such as Postgres
• Experience with Elasticsearch a plus

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 with AWS cloud services: EC2, EMR, S3, RDS, Redshift or experience with GCP