Hiring for AWS Data Engineer at Bay Area, CA (Hybrid) - Need Only Local
John Tin
Please share suitable resumes at Shanka...@relanto.ai
Role: AWS Data Engineer
Location: Bay Area, CA/Hybrid Role/Need Only Local
Job Type: Contract
Job Description:
We are seeking a highly skilled Data Engineer with expertise in modern data platforms, semantic data modeling, and cloud-native lakehouse architectures. In this role, you will be responsible for designing and implementing a scalable semantic data layer that enables self-service analytics, consistent business intelligence, and efficient data access across the organization. You will leverage Dremio, Apache Iceberg, and AWS data services to build high-performance, governed, and scalable data solutions.
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.
Required Skills:
• 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.
Preferred Skills:
• Experience with cloud-native lakehouse architectures and modern data platform ecosystems.
• Familiarity with data catalog and governance tools such as Collibra, Alation, AWS Glue Data Catalog, or similar platforms.
• Experience working with large-scale enterprise analytics and business intelligence environments.
• Knowledge of data orchestration tools such as Apache Airflow or similar workflow platforms.
• Experience with AWS certifications such as AWS Certified Data Engineer or AWS Certified Solutions Architect.
• Familiarity with Python, Spark, or other big data processing technologies.
• Understanding of modern data mesh, data fabric, and self-service analytics principles.
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