onhires - Senior Data Engineer
Requirements
• 4+ years of experience as a Data Engineer. • Hands-on experience with Spark/PySpark. • Experience building production ETL/ELT pipelines. • Strong understanding of data modeling principles. • Experience with workflow orchestration tools such as Airflow. • Experience working with cloud data platforms. • A strong ownership mindset and the ability to work independently. • Professional English. • Delta Lake or Lakehouse architecture. • MongoDB or other NoSQL databases. • CDC and streaming technologies (Kafka, Debezium, etc.). • Data quality frameworks (Great Expectations or similar). • Experience with metadata, lineage, or observability tools. • Familiarity with AI-assisted development (GitHub Copilot, Cursor, Claude Code, etc.).
Responsibilities
• Design, build, and maintain scalable batch and streaming data pipelines. • Develop reliable ETL/ELT workflows using Python, Spark, and modern orchestration tools. • Improve data quality, validation, monitoring, and observability across the platform. • Design data models that support analytics and product development. • Build ingestion pipelines connecting multiple external and internal data sources. • Optimize large-scale processing performance and platform reliability. • Work closely with product managers and engineers to translate business requirements into technical solutions. • Use modern AI-assisted development tools to improve engineering productivity.
Benefits
• Build a modern data platform from the ground up rather than maintaining legacy systems. • Work on technically challenging problems involving large-scale data integration and quality. • Join a highly collaborative engineering team where you'll have real ownership and influence over technical decisions.
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