Suvoda
Data Engineer
Remote Senior $4.7k–$12.8k/moest.
Summary
Suvoda is seeking a skilled Cloud Data Engineer to evolve their data platform towards a data mesh architecture. In this role, you'll design and build domain-oriented data products and support near real-time reporting. You'll work on building and optimizing ETL/ELT pipelines using AWS Glue and PySpark for scalable, high-performance data processing.
What you'll do
- Contribute to the design and implementation of a data mesh architecture using GraphQL APIs to expose domain-owned data products
- Build and maintain a modern AWS-based data lake using S3, Glue, Lake Formation, Athena, and Redshift
- Develop and optimize ETL/ELT pipelines using AWS Glue and PySpark to support batch and streaming data workloads
- Implement AWS DMS pipelines to replicate data into Aurora PostgreSQL for near real-time analytics and reporting
- Support data governance, quality, observability, and API design best practices
- Collaborate with product, engineering, and analytics teams to deliver robust, reusable data solutions
- Contribute to automation and CI/CD practices for data infrastructure and pipelines
- Stay current with emerging technologies and industry trends to help evolve the platform
Requirements
Required:
- Bachelor's degree in a technical field such as Computer Science or Mathematics
- At least 4 years of experience in data engineering, with demonstrated ownership of complex data systems
- Solid experience with AWS data lake technologies (S3, Glue, Lake Formation, Athena, Redshift)
- Understanding of data mesh principles and decentralized data architecture
- Proficiency in Python and SQL
- Experience with data modeling, orchestration tools (e.g., Airflow), and CI/CD pipelines
- Strong communication and collaboration skills
Preferred:
- Master's degree, especially with a focus on data engineering, distributed systems, or cloud architecture
- Hands-on experience in infrastructure-as-code tools (e.g., Terraform, CloudFormation)
- Expertise in AWS Glue and PySpark for scalable ETL/ELT development
- Experience with event-driven architectures (e.g., Kafka, Kinesis)
- Familiarity with data cataloging and metadata management tools
- Knowledge of data privacy and compliance standards (e.g., GDPR, HIPAA)
- Background in agile development and DevOps practices