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Remote, mid-level, and popular Data Engineer title increases applicant competition.
Core data engineering skills transfer across industries, but Rust and real-time AI-pipeline experience raise specificity.
Mandatory 6+ years and strong Rust/Python plus streaming and governance requirements create strict shortlisting filters.
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Build and optimize high-volume data ingestion pipelines and event stream processing to support analytics, product loops, and model training.
Ensure data quality, validation, governance, and privacy compliance (including GDPR) at scale for fast, trustworthy data access.
Develop scalable storage and retrieval systems for real-time and batch data applicable to AI-driven platform learning and feature engineering.
6+ years of experience in data engineering.
Strong proficiency in Rust and Python, with backend polyglot capabilities.
Experience with high-volume data ingestion, streaming, and building fast analytics or query infrastructure that scales.
Work Experience Required: 6+ years in data engineering. No explicit mention of educational or location restrictions except remote work from Ukraine.
Experienced in designing data systems for integrated analytics, product feedback loops, and model training within AI or data platform contexts.
Comfortable working with complex, messy event streams converting them into structured, queryable, and governed datasets.
Practices data lineage, data quality, and privacy controls thoughtfully, with a strategic view on operational and governance challenges in large-scale data environments.