Key skills
Amazon RedshiftAWSAzureBigQueryCloudGoogle Cloud PlatformPythonSQLTerraformAIData EngineeringSnowflakeRedshiftDatabricksGCPGoogle CloudPulumiCloudFormationLambdaAzure FunctionsCloud FunctionsREST APIPerformance OptimizationCI/CD
About this role
Role Overview
- Build and manage data pipelines: ingestion from APIs/files, transformations across layers, schema evolution, and collectors from 10+ external sources
- Design semantic models and hybrid search for AI; own star schema with bridge tables and performance optimization
- Enforce governance: access controls, licensing registry, quality monitoring, and retention for GDPR/CCPA
- Manage cloud infrastructure, monitoring, SLAs, cost optimization, and CI/CD
- Deliver client views, multi-cloud exports, and partner with delivery teams for dashboards and AI tools
Requirements
- 5+ years of data engineering experience with production-scale cloud data warehouses
- Strong proficiency in a modern cloud data warehouse (Snowflake, BigQuery, Redshift, or Databricks)
- Advanced SQL
- Experience building event-driven pipelines on a major cloud provider (AWS Lambda/Step Functions, GCP Cloud Functions, or Azure Functions)
- Experience with dimensional data modeling (star schema, slowly changing dimensions, fact tables) and governed transformation layers
- Familiarity with REST API integration
- Proficiency in Python for pipeline orchestration, data transformation, and cloud SDK usage
- Comfortable with infrastructure-as-code (Terraform, CloudFormation, CDK, or Pulumi)
Tech Stack
- Amazon Redshift
- AWS
- Azure
- BigQuery
- Cloud
- Google Cloud Platform
- Python
- SQL
- Terraform
Benefits
- Flexible schedule with core overlap during US working hours (PST)
- Attractive USD compensation
- Paid vacation, holidays