Data Engineer

MARSHALL WACE SINGAPORE PTE. LTD.; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Marshall Wace Singapore Pte. Ltd. is seeking a Data Engineer to join our Data team that spans across international offices. The role focuses on building and maintaining data ingestion processes and platforms that feed investment decisions and critical operations.

The position involves collaborating with investment, business and technical teams, promoting automation, and delivering scalable, reliable data solutions in a fast-moving environment.

Qualifications

• Broad technical knowledge of data processing and exploration.
• Passion for automation and continual improvement.
• Ability to identify patterns and establish standards to reduce development time.
• Ability to build positive, collaborative relationships across teams and geographies.
• Systematic and methodical approach to problem-solving and debugging.

Responsibilities

• Building easily supportable data ingestion pipelines, platforms and systems.
• Digging into and exploring data; identifying features and issues and communicating them clearly to others.
• Standardisation and development of ingestion methodologies, promoting standards across teams via tools.
• Ensuring systems are effective, reliable, scalable and flexible long-term as business needs grow.
• Supporting, monitoring and improving existing systems and ingestion pipelines.

Skills

Python

C#

Scala

Java

Go

Data processing

Automation

Problem solving

Cross-team collaboration

Tools

SQL

Pandas

Elasticsearch

Kibana

Snowflake

Docker

Kubernetes

Airflow

Dagster

Spark

Hive

Kafka

Job description

Role Overview:

We are looking for an ambitious, enthusiastic and highly motivated Data Engineer to join our Data team that spans across our international offices. Data engineers work closely with almost every team in the firm: investment, business and technical. The team builds and maintains thousands of data ingestion processes of varying complexity, feeding investment decisions and facilitating critical operations. The data team also develops and owns the platforms that run and monitor these processes, tools and libraries within them, and complex systems that model the firm's view of the financial world. The role is fast moving and varied, and will suit someone that enjoys direct business interaction, is delivery focused and works well under pressure.

Responsibilities:

• Building easily supportable data ingestion pipelines, platforms and systems.
• Digging into and exploring data; identifying features and issues and communicating them toothers clearly and concisely.
• Standardisation and development of ingestion methodologies, including promoting those standards to other teams across the firm in the form of tools and libraries
• Ensuring that systems are highly effective for downstream teams, as well as reliable, scalable and flexible over the long term as business needs grow and change.
• Supporting, monitoring and improving existing systems and ingestion pipelines.

Requirements:

• Broad technical knowledge, particularly with respect to the processing and exploration of data and an affinity for learning about new technologies.
• A passion for automation and continual improvement, with a track record of identifying high value automation opportunities.
• Ability to identify patterns and establish standards that reduce development time and increase reliability.
• Ability to build positive and collaborative relationships with colleagues across teams and geographies.
• Systematic and methodical approach to problem-solving and debugging.

Technologies:

• The ideal candidate will have:
• Experience with coding in Python / C# / Scala / Java / Go or equivalent.
• Experience working with a variety of data storage and manipulation tools such as SQL, Pandas, Elasticsearch & Kibana, Snowflake.
• Experience with containerisation and orchestration technologies like Docker / Kubernetes / Helm / Flux.
• Experience with various ETL/ELT technologies such as Airflow /Argo / Dagster / Spark / Hive.
• Additional beneficial skills or experience:
• Familiarity with data visualisation tools.
• Experience with Apache Kafka or similar stream processing platforms and concepts.
• Cross asset financial markets experience - Equities, FX, Options, Futures, Fixed Income.