Data Engineer Team Leader

Department
R&D
Type
Full-time
Level
Location
Israel
About The Position

Fetcherr experts in deep learning, e-commerce, and digitization, Fetcherr disrupts 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 looking for an experienced Data Engineer Team Leader to drive our data engineering efforts and lead a team of skilled data engineers. This role is a blend of hands-on technical leadership and team management, responsible for building and scaling data infrastructure that powers real-time pricing, large-scale data pipelines, and machine learning products.

You will lead the team through architecture decisions, development, and deployment of mission-critical systems—while growing and mentoring a high-performing team.

Responsibilities

Lead a team of data engineers building robust, scalable, and high-performance data pipelines and infrastructure.
Design, build, and maintain distributed data processing workflows (batch & streaming).
Drive best practices for data quality, validation, testing, and observability.
Own and evolve Fetcherr’s data architecture in alignment with business and product goals.
Manage sprint planning, task breakdown, code reviews, and performance feedback for your team.
Contribute hands-on to key development tasks and architecture decisions.
Recruit, mentor, and grow the data engineering team.
About The Position

You'll be a great fit if you have...

BSc or MSc in Computer Science, Engineering, or related field.
6+ years of experience in data engineering, including:
Strong Python development background.
Advanced SQL skills and data modeling experience.
Experience with cloud platforms (GCP preferred; AWS/Azure acceptable).
2+ years in a technical leadership or team lead role.
Strong experience with orchestration tools like Apache Airflow, Prefect, or Dagster.
Hands-on experience with distributed data frameworks: Apache Beam, Spark, or similar.
Familiarity with Docker, CI/CD (GitHub, GitLab).
Proven ability to design and maintain data platforms processing hundreds of terabytes of data.
Strong communication and collaboration skills.
Fluent English (spoken and written).

Nice to Have

Experience with Google Cloud Platform (BigQuery, Dataflow, Pub/Sub).
Experience with ML pipelines or collaboration with data science teams.
Exposure to airline domain, pricing systems, or GDS feeds.
Familiarity with data contracts, versioning, and lineage tools.
Strong foundation in data structures and algorithms.
Experience optimizing pipelines and databases for cost