Senior Data Engineer

Workable workplace: remote; Workable locations: Taipei City, Taiwan. Singapore. Hong Kong, Hong Kong, Hong Kong, Asian TimezonesFull-TimeSenior

Salary not disclosed

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Job Details

Demonstrate strong problem-solving and analytical thinking.
Build robust data quality checks and identify anomalies in ingested data.
Write complex SQL queries and optimize query performance.
Be proficient in Python, Java, or Scala.
Have experience building and maintaining complex ETL pipelines using tools such as Apache Airflow, dbt, or custom scripts.
Understand dimensional modeling, star and snowflake schemas, and normalization and denormalization.
Have experience with data platforms such as Snowflake, Redshift, BigQuery, or Synapse.
Have expert knowledge of Apache Spark, Kafka, Flink, or similar technologies.
Understand data security and privacy standards.
A degree in Computer Science, Engineering, Mathematics, or a related field is preferred.
Familiarity with a major cloud platform and its data services is preferred.
Experience with data quality frameworks, Git or GitHub, infrastructure-as-code tools, containerization or orchestration, data governance, data lineage, catalog tools, observability, or monitoring is preferred.

Design, build, and optimize scalable pipelines for ingesting, transforming, and integrating market data, news feeds, and unstructured data.
Maintain data quality, consistency, and real-time monitoring using data validation tools.
Develop processes to normalize and organize the data warehouse for use across departments.
Apply data management practices that support scalable, available, and efficient data storage.
Ensure infrastructure supports trading and research needs while maintaining data integrity, security, and performance.
Collaborate with research and analytics teams to understand their data needs and build frameworks for data exploration, analysis, and model development.
Create tools for overlaying data from multiple sources.
Optimize hardware and software resources to balance performance with cost control.
Evaluate and adopt suitable technologies and data management practices.

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