This is a position we're hiring on behalf of our client
About This Role:
We are seeking a passionate Analytics Engineer to join our mission of revolutionizing financial services and freeing people from complexity. You will act as a bridge between our business needs and data infrastructure, helping all team members properly and efficiently use data in their processes. This role is crucial for maintaining our customer-centric, data-driven culture that challenges traditional banking.
Key Responsibilities:
1. Data Infrastructure & Modeling
- Design, build, and maintain ETL/ELT pipelines to transform raw data into “analytics-friendly” formats
- Develop core datasets that serve as canonical sources of truth across the organization
- Implement data governance practices and ensure data quality standards
- Optimize data architecture to support rapid business growth and scaling
2. Business Partnership & Strategic Analysis
- Collaborate directly with business stakeholders to understand their needs and translate them into technical solutions
- Conduct deep-dive analyses on customer behavior and product performance
- Drive data-driven decision making across all business domains
3. Analytics & Insights
- Develop statistical models, hypothesis testing, and A/B testing frameworks.
- Create and maintain automated dashboards and KPI metrics.
4. Team Development & Knowledge Sharing
- Act as a data literacy multiplier, helping colleagues improve their analytical capabilities
- Document and promote data best practices across squads
- Spend 20% of time on strategic company-wide data integration projects
Requirements
1. Technical Skills:
- Programming: Strong SQL expertise including complex queries, CTEs, window functions, and optimization
- Languages: Proficiency in Python or PySpark for data manipulation and analysis
- Statistics: Solid foundation in statistical analysis, hypothesis testing, and experimental design
- Data Visualization: Experience with BI tools (Looker preferred, Tableau, or similar)
- Experience with Databricks
2. Business & Financial Services
- 6-7 years of experience in analytics engineering, with 2+ years experience in financial services, fintech, or banking environment
- Understanding of credit risk, lending products, and regulatory requirements
- Knowledge of GDPR and data governance
- Experience with customer lifecycle analytics and retention strategies
3. Core Competencies
- Business Judgment: Ability to make strategic and operational decisions using data
- Problem-Solving: Tackle complex problems involving business, regulatory, and operational variables
- Communication: Exceptional ability to influence stakeholders and present data convincingly
- Collaboration: Experience working cross-functionally with non-technical teams
*Preferred Qualifications
- Bachelor’s degree in Mathematics, Statistics, Economics, Computer Science, or related quantitative field
- Experience with big data technologies and cloud platforms
- Machine learning and AI knowledge
- Previous experience in high-growth startup environments
- Familiarity with data modeling using statistical algorithms
- Experience building automated testing and monitoring systems
Benefits
- Meal and parking allowance
- Full benefits and salary rank during probation
- Insurances as Vietnamese labor law and premium health care for you and your family
- Performance bonus up to 2 months
- 13th month salary pro-rata
- 15-day annual leave+ 3-day sick leave + 1 birthday leave + 1 Christmas leave
- SMART goals and clear career opportunities (technical seminar, conference, and career talk)
- Values-driven, international working environment, and agile culture
- Overseas travel opportunities for training and working related
- Internal Hackathons and company’s events (team building, coffee run, blue card…)
- Work-life balance 40-hr per week from Mon to Fri