Data Engineer (Fivetran/Snowflake/dbt)

Location: Remote work available from Brazil, Bulgaria, Colombia, Cyprus, Latvia, Mexico, Poland, Remote LATAM countries, Romania, Serbia, and Uruguay

Company

hirify.global.

What you will do

• Design end-to-end data ingestion and transformation pipelines with Fivetran, dbt, and Snowflake.
• Configure and manage connectors for SaaS applications, databases, APIs, and file-based sources.
• Develop dbt models, tests, freshness checks, incremental processing, documentation, and reusable macros.
• Build optimized Snowflake SQL and analytical data models, including security, RBAC, stages, data loading, and data sharing.
• Implement data quality, reconciliation, monitoring, operational alerting, and production troubleshooting.
• Collaborate with application, infrastructure, security, analytics, and business teams on data-source onboarding and enterprise deployments.

Requirements

• 5+ years of experience in data engineering or a related field.
• 2+ years of hands-on experience with Snowflake and dbt, plus production experience with Fivetran pipelines.
• Strong SQL skills, including complex joins, CTEs, window functions, reconciliation, and query optimization.
• Experience with Python for data processing, automation, API integrations, file processing, validation, and operational scripting.
• Experience with Git, CI/CD, code reviews, automated deployments, and enterprise DEV, QA, and PROD processes.
• Comfort using Claude, Cursor, or VS Code with AI-assisted development capabilities.

Nice to have

• Experience with Apache Airflow or AWS MWAA and AWS services such as S3, IAM, Lambda, Secrets Manager, and FSx.
• Experience integrating Salesforce, Marketo, REST APIs, SFTP, and other SaaS or file-based sources.
• Knowledge of Snowpark, Snowpark Container Services, Databricks, Terraform, or infrastructure as code.
• Experience with Snowflake Secure Data Sharing, data quality and observability frameworks, or legacy ETL modernization.

Culture & Benefits

• Collaboration within a medium-sized team of 10–20 people.
• Cross-functional work with application, infrastructure, security, analytics, and business teams.
• Focus on reliable data delivery, controlled deployments, code review, and CI/CD practices.