Data Engineer

• Collection of performance and operational data from customer product deployment and management platforms.
• Enabling analytics to understand feature utilization and customer satisfaction.
• Supporting proactive risk mitigation campaigns and customer enablement through targeted communications.
• Secure collection and handling of telemetry data with customer privacy considerations. 

Your Impact 

• Snowflake objects such as databases, schemas, tables, views, and store procedures.
• Design, develop, and implement scalable and efficient data pipelines using AWS services (e.g., S3, EC2, ECS, Aurora).
• Write high-quality, maintainable Python code for data extraction, transformation, and loading (ETL) and Machine leaning / AI (LLM) processes.
• Develop and integrate with Web Services, Micro Services, and APIs to ingest and expose data from various internal and external sources.
• Implement robust Data Engineering solutions, including data modeling, database design, and data warehousing.
• Optimize data storage, retrieval, and processing for performance and cost-efficiency on AWS.
• Monitor and troubleshoot data pipeline issues, ensuring data quality, integrity, and availability.
• Collaborate with data scientists, analysts, and software engineers to understand data requirements and deliver solutions.
• Contribute to the development and enforcement of data governance policies and standards.
  • Stay up-to-date with emerging technologies and industry trends in Data Engineering, cloud computing, and data management.