At blubank, we’re always looking for curious, capable, and driven people to join our team. As an Analytics Engineering Team Lead, you’ll have the opportunity to work in a fast-paced environment, take on meaningful challenges, and grow alongside a team that values learning, collaboration, and impact.

If you’re excited to build, learn, and make a difference, we’d love to hear from you.

Responsibilities:

• Team Leadership & Development: Lead, mentor, and develop Analytics Engineers. Establish clear ownership, provide technical guidance, conduct code reviews, and foster a culture of accountability, collaboration, and continuous improvement.
• Analytical Data Architecture: Own the design and evolution of analytical data models, including facts, dimensions, aggregations, and materialized views, ensuring scalability, consistency, and reusability across business domains.
• Data Transformation & Engineering: Oversee the development of modular, maintainable, and high-performance SQL-based transformations that convert raw banking data into trusted, analytics-ready datasets.
• Pipeline Orchestration & Reliability: Ensure the reliability and scalability of automated data workflows, including scheduling, dependency management, monitoring, error handling, recovery, and delivery of data within agreed service levels.
• Performance & Scalability: Drive query optimization, database performance tuning, and efficient storage and processing strategies across relational and columnar databases, balancing performance, reliability, and infrastructure costs.
• Data Quality & Observability: Establish standards and automated mechanisms for data validation, freshness monitoring, anomaly detection, and pipeline observability. Ensure data issues are identified, prioritized, and resolved proactively.
• Semantic Layer & Metric Governance: Lead the standardization of business definitions, KPIs, and reusable analytical logic, ensuring consistent metric interpretation across dashboards, reports, and analytical products.
• Technical Standards & Best Practices: Define and enforce engineering standards for version control, code reviews, testing, documentation, deployment, and maintainability. Promote automation and continuous improvement across the development lifecycle.
• Planning & Delivery: Translate business and analytical requirements into technical roadmaps, prioritize work based on business impact and technical risk, manage dependencies, and ensure predictable delivery of engineering commitments.
• Documentation & Governance: Ensure appropriate documentation of data models, business logic, data lineage, ownership, and operational procedures, supporting transparency, auditability, and long-term maintainability.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Engineering, Industrial Engineering, Mathematics, Statistics, or a related quantitative or technical field
• At least 5 years of relevant experience
• Experience in analytics engineering, data engineering, BI engineering, or related data-intensive roles

Benefits:

• Flexible working hours
• Learning, training, and professional development opportunities
• Supplementary health insurance
• Performance-based bonuses
• Employee loans
• Lunch allowance
• Team activities budget
• Military service replacement project for selected positions