Data Engineer – Cloud‑Native Data Ingestion on AWS

About the role

The Data Engineer will design and operate scalable data ingestion pipelines for Origami’s multi‑tenant SaaS platform, migrating legacy C# .NET processes to a cloud‑native architecture on AWS. You will enable clients to feed data via APIs and file uploads, transform it, and load it into SQL Server and Databricks for analytics.

Key responsibilities

• Design and implement data ingestion pipelines using AWS services such as S3, Lambda, API Gateway, Glue, and Step Functions.
• Build API endpoints and file‑upload mechanisms for client data intake.
• Develop mapping and transformation workflows to load data into SQL Server client databases.
• Contribute to a lakehouse architecture on Databricks, ensuring seamless data flow from the SaaS platform to analytical workloads.
• Optimize ETL/ELT processes for performance, reliability, and cost efficiency.
• Collaborate with analytics, software engineering, and product teams to meet business requirements.
• Provide operational support and troubleshooting for existing C# .NET ingestion processes.
• Document architecture, workflows, and operational procedures while enforcing data governance, security, and compliance.

Required profile

• Legal right to work in the Dominican Republic.
• Strong English reading and writing skills.
• Proven experience building data pipelines on AWS.
• Hands‑on programming in Python and/or C# .NET.
• Experience with SQL Server and relational database concepts.
• Familiarity with Databricks, Spark, and lakehouse architectures.
• Solid understanding of ETL/ELT design patterns and data modeling.
• Ability to work collaboratively in cross‑functional teams.

Required skills

• AWS S3
• AWS Lambda
• AWS Glue
• AWS Step Functions
• AWS API Gateway
• Python
• C# .NET
• SQL Server
• Databricks
• Apache Spark
• Lakehouse architecture
• ETL/ELT design patterns
• API development
• File‑based ingestion solutions