- Experience
- 3+ yrs
- Salary
- —
- Openings
- 1
- Posted
- 2 days ago
- Work mode
- In office
- Education
- Bachelor's degree
- Resume
- Required to apply
Where you'll work
Sign in to tell us what does and doesn't work for you here — it sharpens every match we show you.
Job description
Role Overview
We are looking for a skilled Data Engineer to design, develop, and maintain data marts that support comprehensive business analytics and reporting. The successful candidate will be responsible for building optimized ETL/ELT data pipelines and translating business needs into effective dimensional data models such as star and snowflake schemas. Ensuring data quality, consistency, and reliability is vital, alongside query and storage optimization for efficient data consumption.
Key Responsibilities
- Develop, implement, and support data marts tailored for business intelligence and reporting.
- Create and enhance ETL/ELT workflows leveraging scalable data processing technologies.
- Convert business requirements into dimensional data models following established methodologies.
- Maintain data accuracy, coherence, and trustworthiness across data sources.
- Improve query execution and data storage for optimal downstream usage.
- Engage collaboratively with business teams such as Sales, Finance, and Operations to deliver actionable data sets.
- Partner with Data Analysts and BI teams to facilitate self-service analytics capabilities.
- Establish and uphold data governance policies, thorough documentation, and industry best practices within data management.
- Monitor pipeline performance regularly and address any data-related issues promptly.
Qualifications and Experience
- Bachelor's degree or higher in Computer Science, Software Engineering, Statistics, or related disciplines.
- Minimum of three years professional experience in data engineering or data warehouse development, with proven capabilities in building data marts or warehouses end-to-end.
- Expertise in data mart and warehouse modeling, preferably with Kimball methodology.
- Hands-on experience utilizing Databricks technologies including Spark and PySpark.
- Competency in AWS data services such as S3, Glue, Redshift, and Lambda, tailored to technology stacks.
- Strong command of SQL and at least one programming language, preferably Python.
- Demonstrated ability to construct and manage ETL/ELT pipelines effectively.
- Knowledgeable in data partitioning, indexing techniques, and performance optimization strategies.
- English communication skills are essential; proficiency in spoken Chinese is an asset to engage with regional teams and external parties.
Minimum education
Bachelor's Degree