Data Engineer - Data Platform & AI Enablement

Prague, Czech Republic · Prague · 1-3 years experience · Onsite · Posted Oct 8, 2026

At a glance

Everpure is seeking a Data Engineer to help build the foundation for an AI-driven, self-service analytics ecosystem.
The role involves designing and implementing scalable Snowflake data pipelines, delivering curated data assets, and establishing robust metadata and data lineage.

Develop, test, and deploy robust data pipelines into Snowflake using Python (Snowpark) and Apache NiFi to support evolving AI and analytics infrastructure.
Embed metadata generation, automated data lineage tracking, and strict data ownership definitions into every pipeline to guarantee data trust for self-service dashboard creators.
Write clean, efficient SQL to transform raw data into curated assets.
Assist in designing scalable data models optimized for business intelligence and AI workloads.
Monitor pipeline health and tune database performance.
Optimize complex queries and Snowflake warehouse configurations to ensure fast, cost-effective data retrieval.
Work alongside a collaborative team of data engineers, data scientists, and analysts to bridge the gap between raw data sources and actionable, user-facing datasets.

1–3 years of hands-on experience in data engineering, data warehousing, or software development with a heavy data focus.
Strong proficiency in Python.
Hands-on experience with (or a strong desire to learn) Snowflake’s Snowpark framework.
Practical experience with Apache NiFi for data routing, transformation, and system mediation.
Strong working knowledge of advanced SQL, relational databases, and modern cloud data warehouses.
Solid understanding of data modeling principles and how to structure data for both analytical reporting and machine learning consumption.
Familiarity with database performance tuning, query optimization, and execution plan analysis.
A strong understanding of data governance concepts, specifically why metadata, lineage, and ownership are critical in a modern data stack.

Primarily an in-office environment expected to work from the Prague office in compliance with company policies.