Zimetrics - Data Engineer - Python/ETL

Overview

• Hands-on experience in data engineering and distributed systems
• Experience with AI-assisted coding tools (Claude Code, GitHub Copilot, Cursor AI)
• Strong expertise in ClickHouse for analytics, including data modeling, partitioning, indexing, and query optimization.
• Proven ability to design and manage denormalized OLAP datasets to support BI and reporting workloads.
• Solid understanding of ETL/ELT pipelines and experience with tools such as Airbyte, DBT, Airflow or Python-based transformations.
• Proficiency in SQL (advanced queries, performance tuning, window functions, aggregations).
• Hands-on experience working with reporting/visualization frameworks (e.g., amCharts or similar libraries).
• Strong foundation in data quality, governance, and validation to ensure reliable analytics.
• Strong knowledge of real-time data streaming (Kafka, Spark)
• Experience with relational and analytical databases (Postgres, ClickHouse, Elasticsearch)
• Exposure to ML model integration, MLOps is a strong plus
• Strong problem-solving, debugging, and cross-team collaboration skills
  
  

(ref:hirist.tech)