Software Engineering – Data Engineer (Python & Cloud Databases)

Location: Work from Home, United States

Targeted base pay range: $84,000–$132,000 per year

Company

hirify.global is a global analytics software company providing decision-making, credit-scoring, fraud-detection, and lending solutions to businesses in more than 100 countries.

What you will do

• Design, build, secure, operate, and support SQL Server, Amazon Redshift, and other cloud databases powering myhirify.global.com.
• Build and maintain Python ETL/ELT pipelines across operational systems, data warehouses, and analytics platforms.
• Explore data in Jupyter notebooks, prepare datasets for ML and AI applications, and productionize monitored pipelines.
• Tune queries, indexes, schemas, and workloads to resolve latency, blocking, and deadlocks on a high-traffic consumer site.
• Use AI coding assistants, LLMs, and agentic workflows while reviewing and refining generated output.
• Partner with product and marketing teams to modernize data environments and support analytics and AI use cases.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, with demonstrated experience in data and database engineering.
• Hands-on Microsoft SQL Server administration, including configuration, security and permissions, backup and recovery, index and statistics maintenance, monitoring, and HA/DR.
• Expertise writing and tuning complex SQL queries and stored procedures, plus PowerShell scripting for SQL Server backups, restores, environment refreshes, and deployments.
• Strong Python for data engineering, including pandas, NumPy, SQLAlchemy, or PySpark; Jupyter experience; transformation pipelines; and data warehouse modeling.
• Hands-on Amazon Redshift administration and tuning, including distribution keys, sort keys, workload management, and permissions.
• Experience running and securing AWS data platforms such as S3, Glue, Lambda, and RDS, including encryption and access control for sensitive consumer data.
• Experience with workflow orchestration such as Airflow or Step Functions and CI/CD for database and pipeline code.
• Production ownership covering code review, release management, on-call support, communication, and Agile/Scrum collaboration.

Nice to have

• Data pipelines for AI applications, including RAG workflows, vector stores, and MCP server integrations.
• ML tools such as scikit-learn or SageMaker, NoSQL databases, infrastructure as code, BI tools such as Tableau, and/or AWS certifications.

Culture & Benefits

• Inclusive, people-first environment guided by ownership, customer focus, and mutual respect.
• Professional development through learning experiences and opportunities to leverage individual strengths.
• Competitive compensation, benefits, and rewards programs.
• Work/life balance, employee resource groups, and social events.
• Equal employment opportunities are offered to candidates regardless of protected characteristics.