Data Engineer
Netanya, Center District, IL
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Fetcherr
We offer an AI technology based on algo-trading methodologies that empowers our airline partners to redefine the way they price flights to maximize profit and optimize workflow.Description
Fetcherr, experts in deep learning, algo, e-commerce, and digitization, is disrupting traditional systems with its cutting-edge AI technology. At its core is the Large Market Model (LMM), an adaptable AI engine that forecasts demand and market trends with precision, empowering real-time decision-making. Specializing initially in the airline industry, Fetcherr aims to revolutionize industries with dynamic AI-driven solutions.
Fetcher is seeking a Data Engineer to build large-scale optimized data pipelines using cutting-edge technology and tools. We're looking for someone with advanced Python skills and a deep understanding of memory and CPU optimization in distributed environments. This is a high-impact role with responsibilities that directly influence the company's strategic decisions and data-driven initiatives.
Key Responsibilities:
- Build and optimize ETL/ELT workflows for analytics, ML models, and real-time systems
- Implement data transformation using DBT, SQL, and Python
- Work with distributed computing frameworks to process large-scale data
- Ensure data integrity and quality across all pipelines
- Optimize query performance in cloud-based data warehouses
- Automate data processes using orchestration tools
- Monitor and troubleshoot pipeline systems
Requirements
You’ll be a great fit if you have...
- 4+ years of hands-on experience building and maintaining production-grade data pipelines at scale
- Expertise in Python, with strong grasp of data structures, performance optimization, and modern data processing libraries (e.g. pandas, NumPy)
- Practical experience with distributed computing frameworks such as Dask or Spark, including performance tuning and memory management
- Proficiency in SQL, with a deep understanding of query optimization, analytical functions, and cost-efficient query design
- Experience designing and managing transformation logic using dbt and Dask, with a focus on modular development, testability, and scalable performance across large datasets
- Strong understanding of ETL/ELT architecture, data modeling principles, and data validation
- Familiarity with cloud platforms (e.g. GCP, AWS) and modern data storage formats (e.g. Parquet, BigQuery, Delta Lake)
- Experience with CI/CD workflows, Docker, and orchestrating workloads in Kubernetes
Advantages:
- Dagster or similar orchestration tools
- Testing frameworks for data workflows (pytest, Great Expectations)
- Performance optimization skills, especially for Dask/pandas
- Cross-client solution design focusing on efficiency
- Software architecture best practices (SOLID principles)
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture AWS BigQuery CI/CD Dagster Data pipelines dbt Deep Learning Docker E-commerce ELT ETL GCP Kubernetes Machine Learning ML models NumPy Pandas Parquet Pipelines Python Spark SQL Testing
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