Fetcherr is an AI-driven company specializing in deep learning, algorithmic trading, and large-scale data solutions. Our core technology, the Large Market Model (LMM), enables accurate demand forecasting and real-time, data-driven decision-making. Originally focused on the airline industry, Fetcherr is expanding its AI solutions across additional industries.

We are seeking an experienced Data Engineer Team Lead 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

• Manage a team of data engineers responsible for 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.

Requirements:

• 3+ years of proven experience leading and managing a team of data engineers (people management is required)
• 6+ years of experience in data engineering, including a 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)

Nice to Have

• 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