Senior Data Engineer (Cloud Data)

Location: US-based, remote or hybrid; must be authorized to work in the United States.

Company

hirify.global designs and delivers scalable digital solutions and complex software projects for global companies, from architecture through execution.

What you will do

• Design, build, and deploy scalable, decoupled, high-performance pipelines for batch and streaming ingestion into data lakes and data warehouses.
• Develop and optimize ETL/ELT pipelines using Python, PySpark, and advanced SQL.
• Collaborate with Data Scientists and ML Engineers to automate MLOps workflows and collect model interaction data for retraining loops.
• Monitor, troubleshoot, and optimize pipeline execution, query performance, and cloud storage utilization across AWS and GCP.
• Implement data quality frameworks, testing controls, governance, and integrity checks for raw and curated datasets.
• Apply DevOps and MLOps practices, maintain CI/CD pipelines, use Docker, and document technical standards and architectures.

Requirements

• 5+ years of Data Engineering experience with a proven record of designing and operating large-scale data systems.
• Mastery of Python and advanced SQL, including query optimization and performance tuning.
• Hands-on experience with AWS services including Redshift, Glue, EMR, MWAA, and S3, or GCP BigQuery, plus modern processing engines such as PySpark.
• Proficiency with UNIX environments, Docker, Git, and CI/CD pipelines.
• Solid understanding of data structures, batch and streaming processing, and familiarity with MLOps or the ML deployment lifecycle.
• Excellent verbal and written English communication skills.

Nice to have

• Experience with Infrastructure as Code, such as Terraform.
• Experience building and maintaining scalable REST APIs.
• Exposure to prompt engineering workflows or generative AI data pipelines.

Culture & Benefits

• Remote-first work environment with remote or hybrid options for US-based employees.
• Collaboration with international teams and partners.
• Autonomy, clear communication, technical excellence, and collaborative work.
• Inclusive and challenging environment with opportunities for growth.
• Fair compensation and technology projects designed to create measurable impact.