Data Engineer Team Leader

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.

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