Data Engineer

As a Data Engineer, you will be responsible for designing, building, and maintaining scalable and efficient data pipelines, SQL databases and consolidated Excel/Access data sets. Your key role is to script ETL pipelines to data stores from a multitude of sources both from internal systems, 3rd party systems as well as publicly available sources such as Google analytics. These data stores form the foundation for our goal of real-time dashboards, metrics tracking, and identify emerging trends to drive data-driven decisions across the business.

Key Responsibilities

1. Design, build, and maintain robust and scalable data pipelines to collect, process, and store structured and unstructured data from various sources.
2. Develop and optimize database schemas, tables, and queries to support data storage, retrieval, and analysis.
3. Implement ETL processes to integrate data from various sources, ensuring data quality, consistency, and integrity.
4. Monitor and troubleshoot data pipelines and infrastructure issues and provide timely resolutions.
5. Develop real-time reports and dashboards using BI tools (e.g., Tableau, Power BI, Looker).
6. Collaborate with Business Insights Analyst and other cross-functional team members to understand data requirements, perform data profiling, and implement data transformation and cleaning processes.

Qualifications

1. Bachelor’s degree in Data Science, Information Systems, Computer Science, Engineering, Statistics, or a related field.
2. Proven experience as a data pipeline engineer in various functional teams such as Business Intelligence, Data Analytics, or a similar role.
3. Advanced Excel skills (such as VBA scripting, macros, array formulas, pivot tables, power queries, multi-data source integration, data cleansing methods, text and data manipulation functions, charting and dashboarding) and seasoned in large data validation, reconciliation, and management.
4. Strong Relational Database and SQL Scripting skills with the ability to extract and manipulate large data sets.
5. Proficiency in BI tools (Tableau, Power BI, Looker, or similar) is an advantage.
6. Experience with real-time data processing and streaming technologies (e.g., Apache Flink, Kafka Streams) is not required but a strong advantage.
7. Experience with cloud data platforms (BigQuery, Snowflake, Redshift) is a plus.
8. Strong problem-solving skills and ability to identify actionable insights.
9. Excellent communication skills – able to present data-driven recommendations to non-technical stakeholders. Bilingually strong in English and Chinese is an advantage in order to support Chinese speaking stakeholders.