Role Overview
We are hiring an experienced Data / Analytics Engineer to build scalable data pipelines, work across modern cloud data platforms, and integrate AI/LLM capabilities into production workflows.
What You Will Do
Build and maintain large-scale data ingestion and transformation pipelines, develop production workflows, build and optimize dbt models, design and manage Apache Iceberg tables, implement infrastructure as code, optimize data pipelines, integrate LLMs into production workflows, build LLM-powered features, manage data quality, monitoring, incident resolution, and automated testing.
Why It Might Be a Fit
Must-have skills include 5+ years in Data Engineering or Analytics Engineering, strong Python and advanced SQL, hands-on experience with dbt and Apache Airflow, AWS data services, experience with Snowflake, Spark/PySpark, and lakehouse technologies, strong Terraform / Infrastructure-as-Code experience, production LLM integration, and strong data modeling, pipeline reliability, and data-quality practices.
Requirements
- 5+ years in Data Engineering or Analytics Engineering
- Strong Python and advanced SQL
- Hands-on experience with dbt and Apache Airflow
- AWS data services: S3, Lambda, Glue, Step Functions, and related services
- Experience with Snowflake, Spark/PySpark, and lakehouse technologies
- Strong Terraform / Infrastructure-as-Code experience
- Production LLM integration, including API handling, retries, rate limits, and cost optimization
- Prompt engineering, LLM evaluation, and regression testing
- Strong data modeling, pipeline reliability, and data-quality practices
- Experience using AI coding agents such as Claude Code or similar
To apply for this job please visit linkedin.com.
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