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 seeking an experienced Data Engineer Team Leader to lead our data engineering efforts and oversee a team of skilled data engineers. This role combines hands-on technical leadership and team management, with responsibilities that include building and scaling data infrastructure to power 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.
  
  

• 6+ years of experience in data engineering, including 3+ years in a technical leadership or team lead role
• Strong Python programming background
• Advanced SQL skills and data modeling experience
• Proven experience designing and maintaining large-scale data platforms (hundreds of TBs)
• Expertise with data orchestration tools (Airflow, Prefect, or Dagster)
• Hands-on experience with distributed data frameworks (Apache Beam, Spark, or similar)
• Cloud platform experience — GCP preferred (AWS/Azure acceptable)
• Familiarity with Docker and CI/CD pipelines (GitHub/GitLab)
• Strong communication, mentorship, and collaboration skills
• BSc/MSc in Computer Science, Engineering, or a related field
• Fluent English (spoken and written)
  
  

• Experience with Google Cloud Platform tools (BigQuery, Dataflow, Pub/Sub)
• Background working with ML pipelines or data science teams
• Understanding of data contracts, lineage, and versioning tools
• Knowledge of data structures and algorithms
• Experience optimizing pipelines and databases for performance and cost
• Exposure to airline, pricing, or GDS systems