Role Summary
The Data Engineer (AMI) is responsible for designing, building, and maintaining the data infrastructure required to support Advanced Metering Infrastructure (AMI) data collection, processing, storage, and analytics. This role ensures robust, scalable, and efficient data pipelines for energy and utility operations.
Responsibilities
- Design and implement data pipelines for AMI data ingestion, transformation, and loading (ETL/ELT).
- Develop and maintain data architectures for large-scale smart meter data processing.
- Optimize data storage solutions (e.g., data lakes, data warehouses) for performance and cost-efficiency.
- Collaborate with data scientists and analysts to enable advanced analytics and reporting.
- Ensure data quality, integrity, and security across all AMI data systems.
- Monitor and troubleshoot data workflow issues to minimize downtime.
- Document data engineering processes and best practices.
Qualifications
- Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.
- 3+ years of experience in data engineering or a similar role.
- Strong proficiency in SQL and Python (or Scala).
- Experience with cloud platforms (AWS, Azure, or GCP) and big data technologies (Spark, Hadoop, Kafka).
- Familiarity with AMI systems and smart grid data is highly desirable.
- Knowledge of data modeling, database design, and data warehousing concepts.
- Excellent problem-solving and communication skills.
Skills
- Data Pipeline Development: ETL/ELT, Apache Airflow, or similar orchestration tools.
- Database Technologies: Relational (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra).
- Cloud & Big Data: AWS (S3, Redshift, Glue), Azure (Data Factory, Synapse), GCP (BigQuery, Dataflow).
- Programming: Python, SQL, Java, or Scala.
- Data Visualization: Tableau, Power BI (preferred).
- Version Control: Git, CI/CD pipelines.