Senior Data Engineer

3 months ago

Hà Nội, Vietnam SHB Finance Full time

Nơi Làm Việc Hà Nội

Cấp Bậc Nhân viên

Hình Thức Nhân viên chính thức

Bằng Cấp Đại học

Kinh Nghiệm 3 - 5 Năm

Mức Lương Lương thỏa thuận

Ngành nghề CNTT - Phần cứng / Mạng, CNTT - Phần mềm, Ngân hàng, Tài chính / Đầu tư

Hạn Chót Nhận Hồ Sơ 31/10/2024

**Phúc Lợi**:

- Bảo hiểm
- Du Lịch
- Phụ cấp
- Thưởng
- Đào tạo
- Tăng lương
- Công tác phí

**Mô Tả Công Việc**:

- Design, develop, and maintain scalable data pipelines and ETL processes to support data ingestion, transformation, and loading from various sources.
- Collaborate with cross-functional teams to understand data requirements and design efficient data models and schema for storage in data warehouses or other data storage solutions.
- Optimize data workflows and processes to ensure high performance, reliability, and scalability of data infrastructure.
- Monitor and troubleshoot data infrastructure to identify and resolve issues proactively, ensuring mínimal disruption to data workflows.
- Conduct performance tuning and optimization of database queries, data processing jobs, and data storage solutions for improved efficiency.
- Stay updated on emerging technologies, tools, and trends in data engineering and recommend innovative solutions to enhance data capabilities and drive business value.
- Document data architecture, processes, and workflows to facilitate knowledge sharing and ensure scalability and maintainability of data solutions.
- Collaborate closely with data analysts to understand analytical requirements and provide support in data exploration, visualization, and interpretation to derive actionable insights for the business.

**A professional and open working environment that values 5 core principles: "Smart - Honest
- Brave
- Friendly - Cooperative”**
- Working hours from Monday to Friday, with a 1-hour and 30-minute lunch break;
- Friendly colleagues who prioritize the personal development of each individual;
- A spacious and well-equipped office space to support your work;
**Special Care for Employees**
- Competitive compensation package with attractive bonuses;
- Variety allowance: lunch (1.200.000 Đ/month), parking support (200.000 Đ/month), mobile phone, business trip...;
- Employee’s birthday leave.
- Exclusive comprehensive health insurance benefits with SHBFC Care;
- Annual health check-ups at top hospitals in Vietnam and statutory social insurance benefits as per state regulations;
- Annual trips and team-building activities.

**Focus on Personal Development Support**
- Receive guidance, mentorship, and career development support from talented and experienced management;
- Opportunities to participate in major projects and be at the forefront of the consumer finance industry;
- Policies to support educational activities, knowledge sharing, and cultural exchange (Training, Seminars, etc.).

**Yêu Cầu Công Việc**:

- Bachelor's degree or higher in Computer Science, Information Technology, Engineering, Mathematics, or a related field.
- Proven experience (3+ years) working as a data engineer, software engineer, or a related role, preferably in the finance or banking industry.
- Strong proficiency in SQL and other programming languages such as Python, Java, or Scala, etc., with the ability to write efficient, clean, and maintainable code.
- Solid understanding of database systems, data warehousing concepts, and proficiency in SQL databases like Oracle, PostgreSQL, MySQL, SQL Server,...
- Knowledge of data modeling principles and experience designing efficient data schemas for relational and non-relational databases.
- Strong analytical and problem-solving skills with the ability to troubleshoot and resolve complex data-related issues.
- Excellent communication and collaboration skills with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.
- Experience with version control systems such as Git and proficiency in Linux/Unix environments.
- Continuous learning mindset with a willingness to stay updated on emerging technologies and best practices in data engineering and analytics.

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