GreenGas USA→
Data Engineer - Intern at GreenGas USA in Houston, TX
InternshipHybridFull-timeHouston, TX
Skills
pythonsqldata warehousingetl toolsazurebig data technologiesdata modelingjavanosql databasesscriptingautomation
Job Description
Summary: GreenGas USA is committed to leading the global energy transition by transforming waste into renewable energy. The Data Engineer Intern will support the organization's data-driven initiatives by assisting in building and maintaining data infrastructure, enabling data accessibility for analysis and reporting.
Responsibilities:
- Design and Implement ETL/ELT Processes: Build robust Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) pipelines to move data from various sources (databases, APIs, streaming sources, external data providers) into data warehouses, data lakes, or other data repositories
- Develop and Maintain Scalable Data Pipelines: Create efficient and scalable data pipelines to handle large volumes of structured and unstructured data
- Automate Data Workflows: Data engineers will write code and scripts to automate repetitive tasks in data collection, processing, and delivery. Ie Databases to PBIs
- Monitor and Troubleshoot Pipelines: Continuously monitor pipeline performance, identify and resolve data-related issues, errors, and performance bottlenecks
- Design and Maintain Data Architecture: Selecting appropriate technologies for data storage such as relational databases, NoSQL databases, data lakes, data warehouses, cloud storage services) and designing efficient data models, schemas
- Optimize Data Storage and Retrieval: Work to ensure data is stored in a way that allows for high-performance queries and efficient analytical and operational use cases
- Evaluate and Implement Data Solutions: Research and implement new data technologies, tools, and frameworks to improve data infrastructure and processes
- Cloud Platform Management: Proficiency in Azure to deploy and manage data solutions in the cloud, including automation, databases and PowerBI’s
- Ensure Data Quality and Integrity: Implement validation rules, cleansing procedures, and monitoring systems to detect and rectify anomalies, ensuring data accuracy
- Implement Data Governance Frameworks: Define standards and policies for data usage, ensuring consistency, reliability, and compliance (e.g., GDPR, HIPAA)
- Manage Data Security and Access: Implement security controls and access management policies to protect sensitive information from unauthorized access or theft
- Provide Data Access Tools: Set up dashboards, analytics tools, and API endpoints to make processed data accessible to end-users and applications
- Document Technical Designs and Workflows: Create comprehensive documentation for data pipelines, architecture, and processes to facilitate system transparency
- Support Data-Driven Decision Making: By providing clean, reliable, and accessible data, data engineers enable organizations to make informed business decisions
Required Qualifications:
- Programming Languages: Python, Java, SQL and related technologies
- Database Systems: Strong knowledge of relational databases (e.g., PostgreSQL, MySQL, SQL Server) and NoSQL databases (e.g., MongoDB, Cassandra)
- Data Warehousing: Experience with data warehousing and platforms (e.g., Snowflake)
- ETL Tools: Proficiency with various ETL tools such as snowflake and Databricks
- Cloud Platforms: Experience with Azure Suite, Jira DevOps and Ticketing system
- Big Data Technologies: (Hadoop, Spark, Kafka, Hive)
- Data Modeling and Schema Design: Ability to design efficient data models
- Scripting and Automation: For automating data processes
Required Skills: Python, SQL, Data Warehousing, ETL Tools
Important Skills: Azure, Big Data Technologies, Data Modeling
Nice-to-Have Skills: Java, NoSQL Databases, Scripting, Automation