Data Engineer

Segantii Capital Management is a global, multi-strategy investment management firm. The Firm was founded in Hong Kong in 2007 and has offices in Hong Kong, London, New York, and Dubai.

We are looking for a motivated self-starter to be a key member of our financial data team.

This individual will be responsible for building out innovative solutions to manage and deliver on the firm's data needs, working together with colleagues globally. This role will also provide exposure to all areas of the business including Investment teams, Quant Developers/Researchers, Risk and Technology.

Key Responsibilities

• Work as part of the firm's financial market data team, which includes both data analysts and data engineers who provide the firm with access to new and existing datasets. The team is responsible for acquisition, cleaning, organisation, analysis, and delivery of data to downstream systems and users
• Work with data vendors and associated counterparties to manage relationships, discover data sets, and ensure compliance with the firm's data governance obligations
• Collaborate with and where required, contribute to broader technology and business initiatives

Skills

• Strong communication skills in order to work with and articulate requirements to different stakeholders
• Basic understanding of financial instruments and derivatives
• Data management skills including modelling, cleaning, delivery, and storage
• Experience working with large datasets, historic or real-time streaming data
• Ability to explain the differences between structured, semi-structure, and un-structured datasets, and how they may be treated differently
• Experience with market data vendors (e.g. Bloomberg, Refinitiv) is a plus

Required Background

• At least 3 years of experience in a relevant role, from either buyside, sellside or a prominent financial market data vendor
• Undergraduate or Masters degree, preferably related to Data Science or Computer Science
• At least 1-2 years of AWS experience would be preferable (ideally AWS cloud practitioner or greater)

Technologies & Methodologies

• Python and commonly used data analysis packages such as Pandas and NumPy
• RDBMS such as Postgres, MSSQL Server
• Knowledge of data storage formats such as JSON, Avro, Parquet
• API middleware technologies such as Flask and FastAPI
• Data distribution technologies such as Kafka, RabbitMQ
• Agile development practices (e.g. Continuous integration, Source control management
• Understanding of test-driven development

Additional Advantageous Languages

• Java (or similar JVM-based language e.g. Kotlin)
• Rust, C or C++
• NoSQL Databases such as MongoDB
• Understands meta programming concepts
• Experience working with data lake or data warehouse technologies