Senior Data Engineer - AWS

Responsibilities

• Design, develop, and maintain enterprise-scale semantic data layers using Dremio to support self-service analytics and business intelligence initiatives.
• Build and manage semantic models, virtual datasets, business views, and curated data products to ensure consistent reporting and analytics across teams.
• Implement and optimize Apache Iceberg-based lakehouse architectures for scalable and reliable data storage and management.
• Leverage Apache Arrow technologies to enable high-performance, columnar query processing and analytical workloads.
• Integrate Dremio with AWS cloud data platforms including Amazon S3, Amazon Redshift, and Amazon RDS.
• Design and implement data virtualization and query federation solutions across multiple data sources.
• Develop and maintain logical and physical data models aligned with business requirements and enterprise data standards.
• Implement data governance, metadata management, data cataloging, and access control frameworks to ensure data quality and compliance.
• Optimize query performance, data access patterns, and workload management across the data platform.
• Collaborate with business stakeholders, analytics teams, and data architects to translate reporting and analytics requirements into scalable technical solutions.
• Support data platform modernization initiatives and promote best practices for data engineering and analytics enablement.

• 5+ years of experience in Data Engineering, Data Warehousing, or Analytics Engineering roles.
• Hands-on experience with Dremio, including semantic layer design, virtual datasets, reflections, and query optimization.
• Strong expertise in SQL, data modeling, and dimensional modeling techniques.
• Experience working with Apache Iceberg for modern lakehouse implementations and table management.
• Solid understanding of Apache Arrow and columnar data processing concepts.
• Experience integrating and managing data platforms on AWS, including S3, Redshift, and RDS.
• Strong knowledge of data virtualization, query federation, and distributed query processing architectures.
• Experience implementing data governance, metadata management, data lineage, and security controls.
• Familiarity with ETL/ELT processes, data pipelines, and large-scale analytical workloads.
• Strong analytical and problem-solving skills with the ability to optimize complex data environments.
• Excellent communication skills and ability to work closely with business and technical stakeholders.