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 scientists and 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 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 science engineering team.
Requirements
Proven experience as a Data Scientist.
Proven experience designing and maintaining large-scale data platforms (hundreds of TBs)
3+ years of proven experience leading and managing a team of data engineers (people management is required)
4+ years of experience in data science, including a strong Python programming background, advanced SQL skills, and data modeling experience
Expertise with data orchestration tools (Airflow, Prefect, or Dagster)
Cloud platform experience – GCP preferred (AWS/Azure acceptable)
Familiarity with Docker
Strong communication, mentorship, and collaboration skills
BSc/MSc in Mathematics/ physics/ statistics/ Computer Science.
Fluent English (spoken and written)
