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AWS Data Engineer

Relanto, Inc.San Jose, CA🇺🇸United StatesPosted 10 Jul 2026

Why This Role Stands Out

Advance your career as an AWS Data Engineer at Relanto, Inc., where you'll design and implement cutting-edge data solutions using Dremio and Apache Iceberg within a hybrid work environment. This role is perfect for a mid-senior professional passionate about building scalable data platforms and enabling self-service analytics. Apply now to contribute to a forward-thinking company and grow your expertise in cloud-native technologies.

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Position: Data Engineer - AWS
Location: Bay Area, CA (Hybrid)
Employment Type: Full-Time

 

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.

 

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.

Skills

SQL
AWS
ETL
Airflow
Apache
Python
Redshift

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