Data Engineer

MERIDIAN & SATURN CAPITAL PTE. LTD.; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Meridian & Saturn Capital Pte. Ltd. in Singapore seeks a data-driven professional to ingest and standardize global equity datasets, enabling robust quantitative research and portfolio construction.

You will collaborate with PMs, researchers, and trading engineers to map tickers, validate data quality, and maintain symbol mappings across markets, exchanges, and asset classes. Experience with Bloomberg/Refinitiv/FactSet is preferred, along with Python, SQL, and Airflow-style pipelines.

Qualifications

• Bachelor's degree or above in Computer Science, Engineering or related field.
• Deep familiarity with global equity markets, including North America, Europe, and Asia-Pacific exchanges.
• Proficiency in Python (Pandas, NumPy), SQL, and data pipeline orchestration tools (Airflow, Luigi).
• Knowledge of major data vendors and experience working with financial reference and pricing data.
• Strong understanding of market microstructure and security identifiers (ISIN, CUSIP, SEDOL, RIC, Bloomberg Ticker).
• Ability to navigate prime brokerage data and internal ticker mapping for order execution and post-trade reconciliation.
• Experience in a data engineering or quantitative data operations role at a hedge fund, prop trading firm, or asset manager.
• Prior experience working with tick- or bar-level data, especially for intraday equity strategies.
• Familiarity with buy-side OMS/EMS systems and order flow handling.

Responsibilities

• Ingest, standardize, and maintain global equity datasets from multiple third-party vendors (e.g., Bloomberg, Refinitiv, FactSet, S&P Global, Exegy, etc.).
• Structure and align data to support quantitative research, factor modeling, and portfolio construction.
• Develop systems to track and handle complex corporate actions including ticker changes, delistings, mergers, spin-offs, dual listings, ADR/local shares.
• Collaborate closely with PMs, quantitative researchers, and trading infrastructure engineers to define and fulfill data requirements.
• Understand prime brokers’ internal ticker conventions and develop robust mappings across trading venues, custodians, and OMS/EMS systems.
• Ensure data quality through rigorous validation, monitoring pipelines, and anomaly detection.
• Help maintain symbol mapping libraries across time zones, exchanges, and asset classes.

Skills

Python

Data analysis

Statistics modelling

Education

Bachelor's degree in Computer Science/Engineering or related field

Tools

Pandas

SQL

Airflow

Luigi

Job description

MS Capital is a private fund management company with a strong founding team of long-accumulated experience in strategy modelling, trading system and platform development, adopting advanced artificial intelligence technology as the cornerstone, and enforcing strict investment management, to achieve sustained and stable returns. We are expending the team, searching for experienced candidates have strong background & skills in programing, statistics modelling, data analysis, etc.

Roles & Responsibilities:

• Ingest, standardize, and maintain global equity datasets from multiple third-party vendors (e.g., Bloomberg, Refinitiv, FactSet, S&P Global, Exegy, etc.).
• Structure and align data to support quantitative research, factor modeling, and portfolio construction.
• Develop systems to track and handle complex corporate actions including ticker changes, delistings, mergers, spin-offs, dual listings, ADR/local shares.
• Collaborate closely with PMs, quantitative researchers, and trading infrastructure engineers to define and fulfill data requirements.
• Understand prime brokers’ internal ticker conventions and develop robust mappings across trading venues, custodians, and OMS/EMS systems.
• Ensure data quality through rigorous validation, monitoring pipelines, and anomaly detection.
• Help maintain symbol mapping libraries across time zones, exchanges, and asset classes.

Qualifications:

• Bachelor's degree or above in Computer Science, Engineering or related field.
• Deep familiarity with global equity markets, including North America, Europe, and Asia-Pacific exchanges.
• Proficient in Python (Pandas, NumPy), SQL, and data pipeline orchestration tools (e.g., Airflow, Luigi).
• Knowledge of major data vendors and experience working with financial reference and pricing data.
• Strong understanding of market microstructure and security identifiers (e.g., ISIN, CUSIP, SEDOL, RIC, Bloomberg Ticker).
• Ability to navigate prime brokerage data and internal ticker mapping for order execution and post-trade reconciliation.
• experience in a data engineering or quantitative data operations role at a hedge fund, proprietary trading firm, or asset manager.
• Prior experience working with tick- or bar-level data, especially for intraday equity strategies.
• Familiarity with buy-side OMS/EMS systems and order flow handling.