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airSlate

Posted 3 months ago

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Data Engineer II (with MLOps)

PolandRemoteFull-time

AI Summary

Data Engineer II collaborates on designing and maintaining scalable data pipelines in AWS, enabling analytics and ML workflows, feature engineering, and MLOps-driven deployment and monitoring.

About this role

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:

  • A Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related technical field — or equivalent practical experience
  • 2-4+ years in Data Engineering, Analytics Engineering, or a backend data-focused role
  • Hands-on experience designing and maintaining data pipelines and data warehouse solutions in AWS
  • Strong SQL — efficient transformations, query optimization, and analytical data modeling
  • Proficiency in Python for data processing and pipeline development
  • Practical experience with ETL/ELT processes, data warehousing concepts (dimensional modeling), and data quality best practices
  • Familiarity with core AWS services such as S3, Redshift, Lambda, and CloudWatch
  • Awareness of ML data preparation and feature engineering workflows — you don't need to build models, but you'll support the people who do
  • Strong analytical thinking, clear communication, and a collaborative mindset across distributed teams
  • Fluent English, written and spoken

    • 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.

    • Skills

    A/b TestingAnalytic DatasetsAWS S3BiCampaign AnalyticsCI/CDCloudWatchData GovernanceData PipelinesData QualityData WarehousingDimensional ModelingELTETLFeature EngineeringLambdaML Data PreparationMLOpsPythonRedshiftSQL

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