Data Engineer

• Design and implement dimensional and normalized data models optimized for analytical workloads in lakehouse environments.
• Build and manage modern data lakehouse solutions using AWS services including Amazon S3, AWS Glue, Amazon Redshift Spectrum, and Lake Formation for governance, cataloging, and fine-grained access control.
• Develop, monitor, and optimize batch and near-real-time data pipelines using AWS Glue, AWS Lambda, Amazon Kinesis, and Step Functions.
• Ingest structured, semi-structured, and unstructured data from APIs, databases, streaming sources, and third-party systems into the lakehouse.
• Define and manage data infrastructure using AWS CloudFormation, CDK, with CI/CD pipelines.
• Support model training and analytics initiatives by preparing datasets, performing analysis with strong attention to detail, and creating visualizations using AWS Quick Suite.
• Perform other duties as assigned.
• Deliver scalable, maintainable data models that support evolving analytical and reporting needs.
• Implement secure, governed lakehouse architecture with centralized metadata, access controls, and auditability via AWS Lake Formation.
• Build high-throughput, fault-tolerant data pipelines with monitoring, alerting, and automated recovery using Amazon CloudWatch and EventBridge.
• Optimize query performance and cost using Redshift, Athena, and S3 partitioning/compression strategies.
• Ensure data quality, lineage, and documentation through automated testing and catalog integration.
• Collaborate effectively with analytics engineers, data scientists, and business stakeholders to align data solutions with organizational objectives.

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