Remote Data Engineer

Required Skills & Experience
• \tSnowflake – Advanced SQL, data modeling, performance optimization, RBAC, stages, and data integration patterns.\n•\tdbt / dbt Cloud – Models, tests, macros, incremental models, sources, documentation, jobs, and deployment patterns.\n•\tFivetran – Connector configuration, schema management, sync troubleshooting, monitoring, and ingestion architecture.\n•\tSQL – Complex joins, CTEs, window functions, reconciliation, and query optimization.\n•\tGit / CI/CD – Branching, pull requests, code reviews, and automated deployment workflows.

Nice to Have Skills & Experience
• \tApache Airflow / AWS MWAA for orchestration.\n•\tAWS services such as S3, IAM, Lambda, Secrets Manager, and FSx.\n•\tSalesforce, Marketo, and other SaaS integrations.\n•\tREST API and SFTP/file-based ingestion.\n•\tSnowflake Secure Data Sharing.\n•\tSnowpark / Snowpark Container Services (SPCS).\n•\tDatabricks.\n•\tTerraform / Infrastructure as Code.\n•\tData quality and observability frameworks.\n•\tExperience modernizing or migrating legacy ETL/integration platforms.\n•\t5+ years of Data Engineering or related experience.\n•\t2+ years of hands-on experience with Snowflake and dbt.\n•\tProduction experience implementing and supporting Fivetran pipelines.\n•\tExperience operating within enterprise DEV → QA → PROD SDLC and change-management processes.\n•\tExperience designing reusable ingestion and transformation patterns.\n•\tStrong production troubleshooting and root-cause analysis skills.

Job Description
• \tDesign, build, and support end-to-end data pipelines using Fivetran, dbt, and Snowflake.\n•\tConfigure and manage Fivetran connectors across SaaS applications, databases, APIs, and file-based sources.\n•\tDevelop and maintain dbt models, including staging, intermediate, mart, and publish layers.\n•\tImplement dbt testing, source freshness, incremental processing, documentation, and reusable macros.\n•\tDevelop optimized Snowflake SQL and scalable analytical data models.\n•\tSupport Snowflake objects, security/RBAC, stages, data sharing, and data-loading patterns.\n•\tImplement data quality, reconciliation, monitoring, and operational alerting.\n•\tTroubleshoot production pipelines and perform root-cause analysis across ingestion and transformation layers.\n•\tParticipate in Git-based development, CI/CD, code reviews, and DEV/QA/PROD deployments.\n•\tCollaborate with application, infrastructure, security, analytics, and business teams to onboard new data sources.\n\nPay range for this position is $65/hr - $75/hr