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BBID Operations
Shenzhen, China2 months ago
English level
B2, upper-intermediate
An email or a Telegram message to the recruiter
At BID Operations, we are passionate about supporting our clients in their journey towards success. Our mission is to empower you to thrive by handling the essential yet time-consuming aspects of your business operations, allowing you to concentrate on strategic growth and innovation. The Data Analyst will be responsible for transforming high-velocity data into the financial narratives that drive our trading strategies. By navigating our real-time pipelines—built on Kafka, RabbitMQ, and ClickHouse—you will ensure that PnL reports and trading analytics are accurate, timely, and insightful. This role sits at the intersection of engineering and finance, requiring a blend of technical analysis and market understanding.
Develop and maintain automated PnL reporting frameworks that pull from real-time data streams. Conduct deep-dive trading analytics to identify execution patterns, slippage, and market impact. Write and optimise complex SQL queries in ClickHouse to handle large-scale financial datasets efficiently. Collaborate with stakeholders to define and implement key performance indicators (KPIs) for various trading desks. Monitor data quality and integrity across the pipeline to ensure financial reporting remains compliant and accurate. Use Python to build robust data processing scripts that automate repetitive analytical tasks. Design data models and schemas that specifically support high-frequency reporting and business objectives.
University degree in Finance, Economics, Computer Science, or a related quantitative field. Prior experience working within the finance or fintech industry, with an understanding of financial instruments or trading data. Advanced SQL knowledge and experience with OLAP databases like ClickHouse. Strong programming skills in Python for data manipulation and automation tasks. Experience with data visualisation tools to represent real-time data effectively. Ability to convey technical findings clearly to both technical and non-technical stakeholders. Detail-oriented mindset with a focus on data accuracy and compliance with governance policies.
Exposure to ClickHouse (or another columnar/OLAP store — Druid, BigQuery, Snowflake) Airflow or similar orchestration; dbt; Git-based workflows BI tooling (Superset, Metabase, Power BI, Grafana)
Competitive salary commensurate with experience. Opportunities for professional development and career advancement. Collaborative and supportive work environment. Flexibility in smart casual dress code.
Company Introduction At BID Operations, we are passionate about supporting our clients in their journey towards success. Our mission is to empower you to thrive by handling the essential yet time-consuming aspects of your business operations, allowing you to concentrate on strategic growth and innovation. About the role The Data Analyst will be responsible for transforming high-velocity data into the financial narratives that drive our trading strategies. By navigating our real-time pipelines—built on Kafka, RabbitMQ, and ClickHouse—you will ensure that PnL reports and trading analytics are accurate, timely, and insightful. This role sits at the intersection of engineering and finance, requiring a blend of technical analysis and market understanding. Job Responsibilities Develop and maintain automated PnL reporting frameworks that pull from real-time data streams. Conduct deep-dive trading analytics to identify execution patterns, slippage, and market impact. Write and optimise complex SQL queries in ClickHouse to handle large-scale financial datasets efficiently. Collaborate with stakeholders to define and implement key performance indicators (KPIs) for various trading desks. Monitor data quality and integrity across the pipeline to ensure financial reporting remains compliant and accurate. Use Python to build robust data processing scripts that automate repetitive analytical tasks. Design data models and schemas that specifically support high-frequency reporting and business objectives. Requirements University degree in Finance, Economics, Computer Science, or a related quantitative field. Prior experience working within the finance or fintech industry, with an understanding of financial instruments or trading data. Advanced SQL knowledge and experience with OLAP databases like ClickHouse. Strong programming skills in Python for data manipulation and automation tasks. Experience with data visualisation tools to represent real-time data effectively. Ability to convey technical findings clearly to both technical and non-technical stakeholders. Detail-oriented mindset with a focus on data accuracy and compliance with governance policies. Nice to have: Exposure to ClickHouse (or another columnar/OLAP store — Druid, BigQuery, Snowflake) Airflow or similar orchestration; dbt; Git-based workflows BI tooling (Superset, Metabase, Power BI, Grafana) Benefits Competitive salary commensurate with experience. Opportunities for professional development and career advancement. Collaborative and supportive work environment. Flexibility in smart casual dress code.
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