Data Engineer

TL;DR

Data Engineer: Designing, building, and maintaining scalable data infrastructure and reliable pipelines with an accent on ETL/ELT processes, data warehousing, and performance optimization. Focus on ensuring data integrity, orchestrating complex workflows, and enabling analytics through high-performance, trustworthy data systems.

Location: Must be based in the United States

Company

hirify.global is a professional sourcing and recruitment partner connecting skilled talent with US-based clients.

What you will do

• Build, maintain, and optimize ETL/ELT pipelines using Python and SQL.
• Orchestrate complex data workflows using tools like Airflow or Prefect.
• Manage and optimize cloud data warehouses such as Snowflake, BigQuery, or Redshift.
• Implement data quality checks, monitoring, and lineage tracking to ensure reliability.
• Collaborate with analysts and data scientists to deliver analytics-ready datasets.
• Automate deployments and manage infrastructure using CI/CD and IaC tools.

Requirements

• 3+ years of experience in Data Engineering or Data Infrastructure roles.
• Strong proficiency in Python and SQL.
• Hands-on experience with modern data warehouses (Snowflake, Redshift, or BigQuery).
• Proven experience with orchestration tools like Airflow or Prefect.
• Must be available during U.S. client business hours.
• Must be based in the United States.

Nice to have

• Experience with dbt for data modeling.
• Knowledge of streaming platforms like Kafka or Kinesis.
• Familiarity with Docker, Kubernetes, and Terraform.
• Background in regulated industries such as fintech or healthcare.

Culture & Benefits

• Full-time remote position.
• Opportunity to work with modern cloud-native data stacks.
• Focus on high-impact data engineering and infrastructure scalability.
• Collaborative environment working across engineering and analytics teams.

Hiring process

• Initial phone screen and recruiter interview.
• Technical assessment (ETL pipeline or SQL optimization).
• Final client interview with the engineering/data team.