Remote Data Engineer

Required Skills & Experience

• Snowflake – Advanced SQL, data modeling, performance optimization, RBAC, stages, and data integration patterns.
• dbt / dbt Cloud – Models, tests, macros, incremental models, sources, documentation, jobs, and deployment patterns.
• Fivetran – Connector configuration, schema management, sync troubleshooting, monitoring, and ingestion architecture.
• SQL – Complex joins, CTEs, window functions, reconciliation, and query optimization.
• Git / CI/CD – Branching, pull requests, code reviews, and automated deployment workflows.

Nice to Have Skills & Experience

• Apache Airflow / AWS MWAA for orchestration.
• AWS services such as S3, IAM, Lambda, Secrets Manager, and FSx.
• Salesforce, Marketo, and other SaaS integrations.
• REST API and SFTP/file-based ingestion.
• Snowflake Secure Data Sharing.
• Snowpark / Snowpark Container Services (SPCS).
• Databricks.
• Terraform / Infrastructure as Code.
• Data quality and observability frameworks.
• Experience modernizing or migrating legacy ETL/integration platforms.
• 5+ years of Data Engineering or related experience.
• 2+ years of hands-on experience with Snowflake and dbt.
• Production experience implementing and supporting Fivetran pipelines.
• Experience operating within enterprise DEV → QA → PROD SDLC and change-management processes.
• Experience designing reusable ingestion and transformation patterns.
• Strong production troubleshooting and root-cause analysis skills.

Job Description

• Design, build, and support end-to-end data pipelines using Fivetran, dbt, and Snowflake.
• Configure and manage Fivetran connectors across SaaS applications, databases, APIs, and file-based sources.
• Develop and maintain dbt models, including staging, intermediate, mart, and publish layers.
• Implement dbt testing, source freshness, incremental processing, documentation, and reusable macros.
• Develop optimized Snowflake SQL and scalable analytical data models.
• Support Snowflake objects, security/RBAC, stages, data sharing, and data-loading patterns.
• Implement data quality, reconciliation, monitoring, and operational alerting.
• Troubleshoot production pipelines and perform root-cause analysis across ingestion and transformation layers.
• Participate in Git-based development, CI/CD, code reviews, and DEV/QA/PROD deployments.
• Collaborate with application, infrastructure, security, analytics, and business teams to onboard new data sources.

Pay range for this position is $65/hr - $75/hr