Data Engineer II, MLOps

Job not on LinkedIn

🕒 March 19

🇵🇱 Poland – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 45%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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airSlate

WebsiteLinkedInAll Job Openings

501 - 1000 employees

💼 Consulting

📦 Logistics

📣 Marketing

💰 $51.5M Series B on 2022-06

Consulting • Logistics • Marketing

airSlate is a software company that empowers users to create, innovate, automate, and digitally transform their workflows. The company focuses on developing solutions that enhance productivity and streamline processes for various organizations.

📋 Description

• 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.

🎯 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. • 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.

🏖️ Benefits

• Flexible working environment • Competitive compensation and stock options • Professional growth and learning • Health and well-being • Family-friendly culture • Giving back • Open communication