Senior Data Scientist

7 days ago

Thành phố Hồ Chí Minh, Vietnam Zalo Full time

Hồ Chí Minh

Full-time

As a communication platform, Zalo makes it easier for family, friends, and co-workers to connect. A Data Engineer working on Zalo products, you have a chance to make a positive impact on more than 50M users by leveraging the power of our data. This role specifically focuses on data pipeline for analytics and machine learning projects.

**What you will do**:
**Data Platform Development (70%)**
**1. Build and Scale Data Pipelines**:

- Design, build, and optimize robust ETL/ELT pipelines to ensure **_high-quality, reliable, and timely data._**:

- Work with large-scale data processing frameworks such as**_ Spark_** and Kafka to enable real-time and batch data workflows.
- Leverage orchestration tools like**_ Airflow_** to manage complex workflows.

**2. Integrate and Maintain Data Systems**:

- Connect diverse data sources to support analytics, product intelligence, and machine learning needs.
- Develop scalable and maintainable data architecture for data lakes and data warehouses.
- Implement **_data quality monitoring,_** validation, and alerting mechanisms using best practices and modern tools.

**Data Insight & Collaboration (30%)**
1. **Translate Business Needs into Data Solutions**:

- Collaborate closely with Product Managers, Analysts, and Data Scientists to **_understand business rules and translate them into efficient data models _**and logic.
- Build and maintain metrics, dashboards, and reports that provide clear visibility into product and user performance.

2. **Enable Stakeholder Self-service**:

- Empower internal teams by building data marts, documentation, and scalable solutions that reduce dependency on engineering for basic queries.

**What you will need**:

- 3+ years of hands-on experience in data engineering involving large-scale data.
- Proven track record of delivering scalable and maintainable data solutions in a production environment.

**Technical Skills**:

- Advanced proficiency in Python (pyspark) and SQL (Spark SQL).
- Strong experience with distributed data processing tools (e.g., Apache Spark, Kafka).
- Experience building data workflows with orchestration tools like Apache Airflow.
- Familiarity with cloud platforms (AWS, GCP, or Azure) and modern data warehousing solutions (e.g., BigQuery, Snowflake, Redshift).
- Understanding of CI/CD pipelines, containerization (Docker), and version control (Git).
- Solid understanding of supervised and unsupervised learning algorithms, feature engineering techniques, and model evaluation metrics is a plus.

**Soft Skills**:

- Excellent communication and stakeholder management skills.
- Ability to work independently and proactively in a fast-paced, dynamic environment.
- Strong analytical thinking, attention to detail, and problem-solving ability.

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