Data Engineer II (with MLOps)

Das ist der Job

Location: Remote (Global), with offices in the United States, Poland, Romania, and Ukraine .

Darum lohnt es sich

Ability to collaborate effectively across teams and translate business needs into technical solutions. Culture & Benefits Flexible working environment with remote and hybrid options across many countries. Comprehensive health benefits, wellness programs, and quarterly Mental Health Days.

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. This role is also available as hybrid in Wroclaw, Poland .

Company airSlate 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. 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. Competitive compensation, performance-based bonuses, and stock options. Investment in professional growth through courses, conferences, and learning resources.

Family-friendly culture with flexibility for parents and company-wide family days. Commitment to charitable initiatives through the airSlate Care programme. #J-18808-Ljbffr