Data Engineer - AWS
Relanto, Inc.
San Jose, United States of America
yesterday
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
SeniorJob location
San Jose, United States of America
Tech stack
Airflow
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Data analysis
Apache HTTP Server
Big Data
Cloud Engineering
Information Engineering
Data Governance
Data Infrastructure
ETL
Data Security
Data Virtualization
Data Warehousing
Dimensional Modeling
Python
Meta-Data Management
Query Optimization
SQL Databases
Systems Integration
Data Processing
Spark
Data Layers
Microsoft Fabric
Data Lineage
Collibra
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Data Management
Data Pipelines
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.
Requirements
- 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.