Data Engineer with Fivetran, Snowflake and dbt

Role overview Build and operate dependable data pipelines for enterprise analytics and business products on a cloud data platform using Fivetran, dbt, and Snowflake. The work spans source onboarding, transformation, quality controls, orchestration, and production support, with development managed through code review and controlled releases. Python and familiarity with AI-assisted coding tools are also part of the role.

Responsibilities - Design end-to-end ingestion and transformation pipelines with Fivetran, dbt, and Snowflake. - Configure connectors for SaaS tools, databases, APIs, and file-based sources. - Develop dbt models across staging, intermediate, mart, and publish layers; add tests, freshness checks, incremental processing, documentation, and reusable macros. - Build analytical models and optimized Snowflake SQL, and support loading, stages, security, RBAC, and data sharing. - Monitor data quality, reconciliation, and pipeline operations; investigate incidents and identify root causes. - Collaborate across application, infrastructure, security, analytics, and business teams, using Git workflows, CI/CD, and AI-assisted development tools.

Requirements - Five or more years of data engineering or related experience, including at least two years working hands-on with Snowflake and dbt. - Production experience implementing and supporting Fivetran pipelines. - Strong SQL skills, including complex joins, CTEs, window functions, reconciliation, and query optimization. - Working Python skills for data processing, automation, APIs, files, validation, and operational scripts. - Experience with Git, pull requests, code review, automated deployments, and enterprise development environments spanning development, QA, and production. - Strong production troubleshooting and root-cause analysis skills; comfort using AI-assisted coding tools.

Nice to have Experience with Airflow or AWS MWAA; AWS services such as S3, IAM, Lambda, Secrets Manager, or FSx; SaaS, REST API, SFTP, or file integrations; Snowflake Secure Data Sharing; Snowpark; Databricks; Terraform or other infrastructure-as-code tools; data observability; or legacy ETL modernization.