Fetcherr

Fetcherr delivers real-time decision intelligence that lets enterprises price and operate against simulated market dynamics to increase revenue and efficiency. It does this via the Large Market Model…

AIAirline Revenue ManagementDynamic PricingGenerative Pricing EngineMarket Predictionfetcherr.io

Fetcherr

AIAirline Revenue ManagementDynamic PricingGenerative Pricing EngineMarket Predictionfetcherr.io

HQNetanya

Team Size233

Open Jobs32

Total Funding$157M

Latest Fundraise9 months ago

Join the Team

Data Engineer

RemoteWarsaw, Mazowieckie, PL

Remote • Warsaw, Mazowieckie, PL

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Frontend Developer

Part-timeHamburg, DE

Part-time • Hamburg, DE

DevOps Engineer

ContractMunich, DE

Contract • Munich, DE

Data Scientist

Full-timeUtrecht, NL

Full-time • Utrecht, NL

Technical Writer

InternshipJerusalem

Internship • Jerusalem

AI Researcher

InternshipHaifa

Internship • Haifa

Machine Learning Engineer

Part-timeManchester, GB

Part-time • Manchester, GB

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.

We are seeking a Data Engineer to join our growing data team to design, build, and maintain data pipelines and infrastructure. You will work on distributed systems, orchestration frameworks, cloud environments, and modern data technologies to ensure that data flows reliably and efficiently across the organization.

Key Responsibilities:

Ensure data quality, integrity, and performance across workflows.
Optimize processes for scalability and efficiency in distributed environments.
Work with cloud-native solutions and containerized environments (Docker/Kubernetes) .
Implement and manage orchestration frameworks (Airflow/Dagster/etc.).
Collaborate with cross-functional teams to support business and research needs.
Develop and enforce CI/CD processes and data testing frameworks (pytest, GE, or similar).
Monitor, troubleshoot, and continuously improve pipeline reliability and performance.

Requirements:

You’ll be a great fit if you have...

4+ years of professional experience with Python and SQL.
Proven experience building and maintaining ETL/ELT pipelines (batch/streaming) with orchestration frameworks (Airflow, Dagster, or similar).
Hands-on experience with distributed computing frameworks (Spark, Dask, Beam) and large-scale data processing.
Experience with major cloud platforms (AWS, GCP, or Azure); GCP/BigQuery is an advantage.
Proficiency with Docker/Kubernetes and CI/CD pipelines (GitLab CI, GitHub Actions, or similar).
Solid understanding of software engineering practices (data structures, algorithms, TDD, code quality).
Familiarity with data testing and monitoring frameworks (pytest, Great Expectations, observability tools).

Nice to Have:

Experience with dbt, ClickHouse, or Ray.
Familiarity with Python data libraries (pandas, NumPy, Apache Arrow, Jinja).
Background in functional programming.
Exposure to ML/AI workflows.