Key skills

AWS Data Engineering S3AWS Data Engineering LambdaAWS Data Engineering GlueAWS Data Engineering Step FunctionsAWS Data Engineering API GatewayPythonC# .NETSQL ServerDatabricks LakehouseApache SparkETL/ELT DesignData ModelingAPI DevelopmentFile-Based Data IngestionCI/CD PipelinesC#CSQL.NETAIMachine LearningETLELTData EngineeringAnalyticsDatabricksSparkAWSAzureLambdaS3GlueBedrockAPI GatewayAzure DevOpsSaaSCI/CDCommunication

About this role

Origami Risk delivers single-platform SaaS solutions for risk, insurance, compliance, and safety management. The Data Engineer will build and scale a cloud-native data platform on AWS and Databricks, developing AI-assisted pipelines and distributed systems that support data products, analytics, data science, and operational use cases.

Responsibilities:

Designs and implements scalable data-ingestion pipelines using AWS services (e.g., S3, Lambda, API Gateway, Glue, Step Functions, Amazon Bedrock, Amazon Agent Core) and Azure DevOps
Builds APIs and file upload mechanisms for client data ingestion
Develops data mapping and transformation workflows for loading into SQL Server client databases
Contributes to the design and implementation of a data Lakehouse architecture leveraging Databricks
Enables seamless data flow from the SaaS platform to the analytical platform
Optimizes ETL/ELT processes for performance and reliability
Collaborates with analytics teams to ensure data availability and quality for reporting and machine learning use cases
Provides operational support for existing ingestion processes integrated into C# .NET code and UI
Troubleshoots and resolves data pipeline issues across environments
Works closely with Software Engineers, Architects, and Product teams to align data solutions with business needs
Implements best practices for data governance, security, and compliance in a multi-tenant environment
Documents architecture, workflows, and operational procedures

Requirements:

- Bachelor's degree in Computer Science, Information Technology, or a related field required
- 5+ years in Data Engineering or related role
- Strong experience with AWS services for data engineering (S3, Lambda, Glue, Step Functions, API Gateway)
- Proficiency in Python and/or C# .NET for data processing and integration
- Hands-on experience with SQL Server and relational database concepts
- Familiarity with Databricks, Spark, and Lakehouse architectures
- Knowledge of ETL/ELT design patterns and data modeling
- Experience building APIs and file-based ingestion solutions
- Exposure to multi-tenant SaaS environments is a plus
- Strong problem-solving and analytical skills
- Ability to work collaboratively in a cross-functional team
- Excellent communication and documentation skills
- Experience with CI/CD pipelines for data workflows
- Knowledge of data governance and security best practices in cloud environments
- Familiarity with modern data integration tools and frameworks
- Exposure to machine learning pipelines and real-time data processing