Data Engineer (DV QES)
Hong Kong
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign, build and maintain scalable pipelines for market and trading data
Clean, validate and enrich raw data for research and production use
Optimize storage, query performance and processing for low latency
Monitor data quality and pipeline health, and troubleshoot issues
Document data flows, schemas and processes for the team
From the employer’s posting
Design, build, and maintain scalable data pipelines for ingesting, processing, and storing large volumes of market and trading data
Clean, validate, and enrich raw data to ensure high quality and consistency for research and production use
Optimize data storage, query performance, and processing workflows to support low-latency and high-throughput requirements
Monitor data quality and pipeline health, troubleshoot issues, and implement improvements
Document data flows, schemas, and processes to support team collaboration and knowledge sharing
What you’ll bring
All qualificationsCore experience
- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field
- Ability to communicate clearly and collaborate effectively with both technical and non-technical teams
- Strong proficiency in Python and SQL for data processing and analysis
- Experience with data pipeline tools and frameworks (e.g., Airflow, Kafka, Spark, or similar)
- Familiarity with relational and non-relational databases, as well as data lake/warehouse technologies
- Solid understanding of data modeling, ETL/ELT processes, and data quality best practices
Preferred experience
- Experience in financial markets or trading data is a plus
Qualification wording
Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field
Ability to communicate clearly and collaborate effectively with both technical and non-technical teams
Strong proficiency in Python and SQL for data processing and analysis
Experience with data pipeline tools and frameworks (e.g., Airflow, Kafka, Spark, or similar)
Familiarity with relational and non-relational databases, as well as data lake/warehouse technologies
Solid understanding of data modeling, ETL/ELT processes, and data quality best practices
Experience in financial markets or trading data is a plus
Education & alternatives
Requirements: - Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field - Strong proficiency in Python and SQL for data processing and analysis
Tools in this posting
- Python
- SQL
- Kafka
- Spark
- Airflow
Source — Tool mentions in context
- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field - Strong proficiency in Python and SQL for data processing and analysis - Experience with data pipeline tools and frameworks (e.g., Airflow, Kafka, Spark, or similar)
- Strong proficiency in Python and SQL for data processing and analysis - Experience with data pipeline tools and frameworks (e.g., Airflow, Kafka, Spark, or similar) - Familiarity with relational and non-relational databases, as well as data lake/warehouse technologies
About DV Trading
Founded two decades ago and headquartered in Chicago, the DV Group of financial services firms has grown to more than 600 people across North America, Europe and Asia.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 29, 2026 · 30 days ago
- Recorded sightings
- 19
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
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Job description
About Us:
Founded two decades ago and headquartered in Chicago, the DV Group of financial services firms has grown to more than 600 people across North America, Europe and Asia. Since becoming an independent proprietary trading firm in 2016, DV Trading has scaled rapidly using its own capital, strategies and risk management to provide liquidity to markets worldwide. DV Group affiliates today include two broker-dealers, a cryptocurrency market maker and a growing investment adviser.
DV Equities is the group's Asia-Pacific equities and futures market-making business, trading cash equities, ETFs, index futures and related products on exchanges across the region.
Overview:
We are looking for a Data Engineer to build and maintain the data infrastructure that powers our trading, research, and risk systems. You will work closely with quantitative researchers, traders, and software engineers to ensure that large-scale market data is clean, reliable, and easily accessible for both real-time trading and historical analysis. This is a hands-on role for someone who enjoys solving data problems in a fast-paced, collaborative environment.
Responsibilities:
- Design, build, and maintain scalable data pipelines for ingesting, processing, and storing large volumes of market and trading data
- Clean, validate, and enrich raw data to ensure high quality and consistency for research and production use
- Optimize data storage, query performance, and processing workflows to support low-latency and high-throughput requirements
- Collaborate with quantitative researchers and traders to understand data needs and deliver efficient data solutions
- Work with software engineers to integrate data pipelines into the firm's trading and research infrastructure
- Monitor data quality and pipeline health, troubleshoot issues, and implement improvements
- Document data flows, schemas, and processes to support team collaboration and knowledge sharing
Requirements:
- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field
- Strong proficiency in Python and SQL for data processing and analysis
- Experience with data pipeline tools and frameworks (e.g., Airflow, Kafka, Spark, or similar)
- Familiarity with relational and non-relational databases, as well as data lake/warehouse technologies
- Solid understanding of data modeling, ETL/ELT processes, and data quality best practices
- Experience working with large-scale datasets and optimizing performance
- Strong problem-solving skills and attention to detail
- Ability to communicate clearly and collaborate effectively with both technical and non-technical teams
- Experience in financial markets or trading data is a plus
DV is not accepting unsolicited resumes from search firms. Only search firms with valid, written agreements with DV should submit resumes in response to DV’s posted positions. All resumes submitted by search firms to DV via e-mail, the Internet, personal delivery, facsimile, or any other method without a valid written agreement shall be deemed the sole property of DV, and no fee will be paid in the event the candidate is hired by DV. DV is proud to be an equal opportunity employer and committed to creating an inclusive environment for all employees.
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- Location & working pattern
Hong Kong
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