Data Engineer II (MLOps, AI)

TL;DR

Data Engineer II (MLOps, AI): Designing and maintaining scalable data pipelines in AWS to power analytics and ML use cases, including ETL/ELT, data quality, and feature engineering with an accent on MLOps workflows for model deployment and monitoring, and enabling AI/LLM-powered capabilities. Focus on designing data infrastructure for A/B testing and measurable experimentation, and ensuring production-grade data delivery for advanced performance analytics.

Location: Remote (Global), with offices in the United States, Poland, Romania, and Ukraine. This role is also available as hybrid in Wroclaw, Poland.

Company

hirify.global is a global SaaS technology company developing no-code workflow automation, electronic signature, and document management solutions that serve hundreds of millions of users worldwide.

What you will do

• Design and maintain scalable batch data pipelines in AWS to power analytics and ML use cases.
• Develop and optimize SQL transformations and analytical datasets for BI and predictive workloads.
• Build reliable ETL/ELT processes with monitoring and data quality checks.
• Create feature-ready datasets and support feature engineering pipelines for ML.
• Contribute to CI/CD-driven MLOps workflows for model deployment and monitoring in AWS.
• Enable integration of AI and LLM-powered capabilities through robust, future-ready data services.

Requirements

• Proven experience designing and maintaining scalable data pipelines in AWS.
• Strong SQL skills and experience building analytical datasets for BI and ML.
• Hands-on experience with ETL/ELT processes and data quality best practices.
• Understanding of ML data preparation and feature engineering workflows.
• Solid knowledge of cloud-based data architecture and cost optimization principles.
• Ability to collaborate effectively across teams and translate business needs into technical solutions.

Nice to have

• Experience contributing to MLOps workflows and CI/CD for ML models.
• Exposure to A/B testing infrastructure and experimentation frameworks.
• Familiarity with AI/LLM integration in product environments.
• Experience in marketing analytics or campaign data pipelines.

Culture & Benefits

• Flexible working environment with remote and hybrid options across many countries.
• Competitive compensation, performance-based bonuses, and stock options.
• Investment in professional growth through courses, conferences, and learning resources.
• Comprehensive health benefits, wellness programs, and quarterly Mental Health Days.
• Family-friendly culture with flexibility for parents and company-wide family days.
• Commitment to charitable initiatives through the hirify.global Care programme.