Data Engineer

Development of robust ETL/ELT data pipelines, ensuring efficient data ingestion, processing, and transformation from diverse sources into AWS data warehouses and data lakes

• Lead the design and development of robust ETL/ELT data pipelines, ensuring efficient data ingestion, processing, and transformation from diverse sources into AWS data warehouses and data lakes. This includes designing and implementing solutions for batch and streaming data, handling various data formats like JSON, CSV, Parquet, and Avro.
• Architect, build, and optimize scalable data architectures, including data lakes (e.g., S3, Delta Lake, Iceberg) and data warehouses (e.g., Redshift, Snowflake) on AWS, ensuring optimal performance and data accessibility.
• Collaborate closely with data scientists, analysts, and other stakeholders to understand data requirements, design appropriate data models and schemas, and deliver tailored data solutions that enable data-driven decision-making.
• Implement advanced data quality and governance practices, ensuring data accuracy, consistency, and compliance with relevant regulations.
• Optimize data retrieval and develop dashboards and reports using various tools, leveraging deep understanding of data warehousing and analytics concepts.
• Proactively identify and resolve operational issues, troubleshoot complex data pipeline failures, and implement evolutionary recommendations for system improvements.
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AWS, Amazon Redshift,DWaaS,Snowflake,business intelligence,cloud computing,cloud providers,data analysis,data management,data processing,data warehouse,information technology,technology