Description & Requirements
The Climate Data Utility Tech Team is actively searching for an experienced Senior Data Engineer to play a pivotal role in the design, implementation, enhancement, and maintenance of scalable data pipelines for the Net-Zero Data Public Utility. These pipelines are essential for the Utility's mission of providing open and accessible public good data through both the Climate Data Utility website and APIs.
A successful candidate will face the challenge of working with data originating from a wide array of sources, each with its own formats, fields, and access protocols. Your responsibilities will encompass the full data lifecycle from the extraction of data from sources, transforming it according to source and domain specific business logic, and pushing it through the Utility’s ingestion process. Additionally, you will be expected to implement data quality checks and validation procedures to ensure the accuracy and reliability of the data provided by the Utility.
Responsibilities:
* Design and develop scalable data pipelines using Python to read from APIs and structured files (Excel, Parquet).
* Translate domain and source specific business logic into efficient code implementations to turn source data into usable structured data for downstream applications.
* Implement data transformations and structuring using tools like Pandas and Pydantic to ensure data quality, consistency, and adherence to business logic requirements.
* Collaborate with data scientists and analysts to support data-driven decision-making.
* Document data engineering processes, including data lineage, data dictionaries, and system architectures
* Maintain best practices through code reviews, version control, and adherence to industry standards.
* Deploy production quality code through CI/CD pipelines into our cloud environment.
* Provide mentorship and guidance to junior team members, fostering their growth and development in data engineering practices.
Qualifications
* 7+ years of experience in data engineering or a similar role.
* Proficiency in Python programming.
* Experience with building and managing data pipelines.
* Knowledge of data warehousing and ETL processes.
* Excellent problem-solving and communication skills.
A successful candidate will face the challenge of working with data originating from a wide array of sources, each with its own formats, fields, and access protocols. Your responsibilities will encompass the full data lifecycle from the extraction of data from sources, transforming it according to source and domain specific business logic, and pushing it through the Utility’s ingestion process. Additionally, you will be expected to implement data quality checks and validation procedures to ensure the accuracy and reliability of the data provided by the Utility.
Responsibilities:
* Design and develop scalable data pipelines using Python to read from APIs and structured files (Excel, Parquet).
* Translate domain and source specific business logic into efficient code implementations to turn source data into usable structured data for downstream applications.
* Implement data transformations and structuring using tools like Pandas and Pydantic to ensure data quality, consistency, and adherence to business logic requirements.
* Collaborate with data scientists and analysts to support data-driven decision-making.
* Document data engineering processes, including data lineage, data dictionaries, and system architectures
* Maintain best practices through code reviews, version control, and adherence to industry standards.
* Deploy production quality code through CI/CD pipelines into our cloud environment.
* Provide mentorship and guidance to junior team members, fostering their growth and development in data engineering practices.
Qualifications
* 7+ years of experience in data engineering or a similar role.
* Proficiency in Python programming.
* Experience with building and managing data pipelines.
* Knowledge of data warehousing and ETL processes.
* Excellent problem-solving and communication skills.