Data Lead

We are looking for a highly motivated and results-driven Data Lead to join our team full-time. In this role, you will shape the vision, architecture, and delivery frameworks for both Data Engineering and Data Science, aligning the teams into a single, high-impact function.

We drive fintech innovation through deep analytical expertise and a data-first, engineering-driven approach.

Key Responsibilities
Data Engineering Leadership
Design and evolve a scalable data platform architecture
Oversee development of robust ETL/ELT pipelines and real-time data streams
Establish engineering best practices: code reviews, CI/CD, data contracts, observability
Drive technology selection and resource planning for ClickHouse, Spark, and supporting infrastructure
Ensure data quality through monitoring, alerting, SLA ownership, and remediation processes
Validate and clean incoming data to maintain high-integrity datasets
Data Science Leadership
Define and lead ML strategy focused on business impact (LTV, churn, recommendations)
Drive advanced feature engineering: transformation, normalization, feature generation
Own model training, hyperparameter optimization, evaluation pipelines, and experiment tracking
Ensure operational stability and observability of ML services
Partner with stakeholders to turn complex challenges into data-driven, Responsible AI solutions
People Cross-Functional Leadership
Communicate effectively across technical and non-technical teams to influence decisions
Lead cross-team processes (e.g., grooming, design reviews, retrospectives)
Mentor team members, create growth plans, and foster a culture of psychological safety and accountability
Requirements
4+ years of hands-on experience in both Data Science and Data Engineering, delivering end-to-end solutions
2+ years of experience managing data teams (hiring, mentoring, performance management)
Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, Electrical Engineering, or a related field
Strong programming skills in Python, with experience writing clean, production-grade code
Solid understanding of software engineering best practices (CI/CD, testing, code reviews, clean architecture)
Practical experience with ML libraries and platforms (e.g., scikit-learn, XGBoost, PySpark)
Deep understanding of core ML algorithms: linear/logistic regression, gradient boosting
Strong foundation in mathematical statistics and probability theory
Proficient in SQL: complex queries, analytical functions, performance tuning
Nice to have
Experience working with ClickHouse or other OLAP databases
Background in the trading domain or financial markets
Experience analyzing and modeling time series data (e.g., price charts, temporal signals)
Familiarity with anti-fraud systems and techniques
We offer
20 paid vacation days per year
10 paid sick leave days per year
Public holidays according to current legislation
Medical insurance
Opportunity to work remotely
Professional education budget
Language learning budget
Wellness budget (gym membership, sports gear and related expenses)