- 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.
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