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Data Engineer II
Nrg Energy
Produces and delivers electricity and energy services across North America via generation and retail brands
Design, build, and maintain robust ETL pipelines for large-scale IoT data at Vivint Smart Home
Documentation and Compliance: Document data processes, pipeline architectures, and system changes. Ensure compliance with data governance and security policies.
Design and Develop ETL Pipelines: Architect, implement, and optimize ETL processes to handle the ingestion, transformation, and storage of large-scale IoT data streams. Ensure data accuracy, consistency, and availability for analysis.
Building and Debugging Data Pipelines
Data Integration and Optimization: Integrate disparate data sources and optimize data storage and retrieval processes to support efficient querying and reporting. Implement best practices for data quality and performance.
Monitor and Improve Data Systems: Continuously monitor the performance of data pipelines and datasets. Identify and address potential issues, and implement improvements to enhance efficiency and reliability.
Collaborate with Stakeholders: Work closely with business users, data scientists, and analysts to understand data requirements and translate them into technical solutions. Provide support and troubleshooting for data-related issues.
Create and Maintain Datasets: Develop and manage comprehensive datasets that aggregate IoT data from various sources. Ensure datasets are well-structured, accessible, and aligned with business needs.
What you bring
data formats
big data
sql
python
cloud
graduate degree
Minimum of 4 years of professional experience in data analysis or data engineering
Graduate Degree in a Quantitative field (Math, Statistics, Engineering, Computer Science) or relevant experience.
Experience with different data formats (Parquet, Arvo, Json, XML, etc.)
Experience with Big Data/Hadoop applications.
SQL experience and strong background in optimizing SQL queries for transforming data
Proficient in Python development for data pipelines and automation, including debugging, testing, and handling development. At least 2 years experience preferred.
Experience with Spark, Hive, Kafka, and Map Reduce
Experience in Linux environments, batch automation, and shell scripts
3+ years work experience.
Distributed systems (pipelines and databases)
Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and data warehousing solutions (e.g., Redshift, Snowflake)
Experience bringing in data from multiple Data Sources / API’s
Benefits
401(k) + Employer Match
Medical/dental/vision/life coverage & 24/7 Medical Hotline
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