Data Engineer (with ML Ops)

About airSlate

airSlate is a global SaaS technology company that develops no-code workflow automation, electronic signature, and document management solutions. Our award-winning products - SignNow, pdfFiller, DocHub, altaFlow, Instapage, and US Legal Forms - serve over hundreds of millions of  users and more than one million customers worldwide, helping organizations of every size digitize processes, improve efficiency, and transform how they work.

We’re in an exciting phase of growth and transformation, with teammates in more than 20 countries across three continents and main hubs in the United States, Poland, Romania, Ukraine and Philippines. 

At airSlate, we’re building value for customers and a culture where growth and innovation go hand in hand. We’re looking for people eager to shape products, scale a company, and thrive in a fast-moving environment.

About the Marketing Engine team:

The marketing team handles comprehensive 360º communication and comprises over 150 people. We manage all aspects in-house and operate a robust automation engine. Our combined monthly traffic across all brands exceeds 31 million. As a marketing team member, you'll play a crucial role in the upcoming phase of our brand's growth as we expand and introduce new products to the market.

What you'll be working on:

• 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 initiatives.

• Deliver production-grade data to support elasticity modeling and advanced performance analytics.

• Design data infrastructure for A/B testing and measurable experimentation.

• Develop ingestion pipelines for marketing and campaign analytics.

• Contribute to CI/CD-driven MLOps workflows for model deployment and monitoring in AWS.

• Collaborate on data governance, cost optimization, and scalable architecture decisions.

• Enable integration of AI and LLM-powered capabilities through robust, future-ready data services.

What we expect from you:

• 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.

• Experience supporting production systems with reliability and performance in mind.

• Solid knowledge of cloud-based data architecture and cost optimization principles.

• Ability to collaborate effectively across teams and translate business needs into technical solutions.

What helps you stand out:

• 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.

• A proactive mindset with a strong sense of ownership and curiosity about emerging AI trends.