Airslate

Data Engineer II (with MLOps)

  • Airslate

Job Description

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.

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