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Cloud Data Engineer

2 months ago

Boston, United States Intelletec Energy Full time

Company Overview:

Provides asset management & optimization services to owners of generation and energy storage in North America, and wholesale energy to utilities and municipalities. Our traders cover competitive power markets including New England, Midwest and Western markets. Driven by a fundamentals-based approach, our team develops and maintains electric-transmission, gas network and supply/demand models to inform market views for trading opportunities.

Opportunity Overview:

Were looking for a Cloud Data Engineer to help transform our cloud data systems by deploying architectures to drive greater analytical and business value from a wide range of data sources. The role will work with the team to design and develop high-performance, resilient, automated data pipelines, and data transformation applications, adapting technologies for ingesting, transforming, classifying, cleansing and exposing data using creative design to meet objectives. The Cloud Data Engineers broad experience with data management technologies will enable matching the right technologies to the required schemas and workloads.

Responsibilities:

  • Work directly with analysts to gain insight into existing data sets. Evaluate use cases for new data turning requests into actionable designs.
  • Build and maintain serverless data ingestion & refresh pipelines in terabyte-scale using Azure cloud services Azure Data Factory, Azure Logic Apps, Databricks, PySpark and Python, Azure SQL DW, Azure Data Lake Store, and others.
  • Incorporate new data sources from external vendors using streams, flat files, APIs and databases.
  • Leverage advanced data modeling skills to design, and develop dimensional model (Facts, Dimensions).
  • Maintain and provide support for the existing data pipelines using Python, ADF, Spark, and SQL.
  • Develop & enhance database architecture of analytical data environment.
  • Recommend & implement optimal designs, choosing between relational, graph, columnar, and document databases based on requirements.
  • Plan & execute using agile methodologies, developing & delivering within predefined sprints.
  • Identify & deploy appropriate file formats for data ingestion into various storage and/or compute services via ADF for multiple use cases.
  • Develop real-time/near real-time data ingestion solutions from web API.
  • Develop and implement tests to ensure data quality across all integrated data sources.
  • Serve as internal subject matter expert & coach team members in use of distributed computing frameworks for data analysis & modeling, including Azure services.

Required Experience and Skills:

  • Bachelors degree in computer science, engineering, or data science.
  • Expert level programming experience in Python (Anaconda/Data Science/Scrapy), and SQL (Complex ANSI-SQL).
  • 4+ years with relational databases (e.g.: PostgreSQL Microsoft SQL Server, MySQL, Oracle).
  • 3+ years of experience designing and developing enterprise data warehouses (Kimball star schema model).
  • 2+ years working with Spark or other distributed computing frameworks (e.g.: Hadoop, Cloudera, Databricks).
  • 2+ years with Azure services including: Logic Apps, Azure Functions, DevOps.
  • Experience with contemporary data file formats like Apache Parquet, Avro.
  • Experience analyzing data for data quality and supporting the use of data in an enterprise setting.
  • Streaming technologies (e.g.: Azure Event Hubs, Kafka) a plus.
  • Distributed SQL query engines (e.g.: Hive, Azure SQL DW, Presto) a plus.