Data Engineer

Design, develop, and maintain highly scalable data infrastructure.
Design data warehouse/data mart and implement appropriate data models depending on different data use cases.
Design, develop, and maintain a single source of truth for key business metrics.
Ensure standardized metadata, access protocols, and discovery mechanisms.
Act as a subject matter expert for data architecture, data modelling, solution design, and best practices within the Data Team.
Develop a good understanding of the Business with its various domains and understand data use cases across different functions.
Build data quality checks and ensure quality of data products, including timeliness, consistency, performance, and accuracy.
Collaborate with the Engineering department on data governance/security standards and ensure that data products meet those standards.
Monitor data collection, storage and retrieval processes.
Explore and integrate appropriate new big data technologies into current infrastructure.

At least 3 years of experience working in data engineering, data architecture, data modelling, master data management, or similar.
In-depth understanding of data pipelines (ETL/ELT), database structure principles, data warehousing techniques, data mining concepts, and segmentation techniques.
Experience in designing and implementing data lake, data warehouse and data mart.
Experience in database performance tuning.
Hands-on experience in SQL and Python.
Passionate and knowledgeable about big data stacks.
Distributed systems: Spark, Hadoop, Presto, Hive, etc.
Message Queuing systems: Kafka, etc.
Database (Relational & NoSQL): PostgreSQL, MySQL, Cassandra, etc.
Workflow Orchestrator: Airflow, etc.
Business Intelligence Tool: Looker, Tableau, etc.
Experience gathering and analyzing both system and business requirements.
Experience with cloud computing platforms (AWS, AliCloud, GCP, or others) and UNIX environment.
Have fast learning capability and natural curiosity about big data.