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 proactive Data Engineer to join the global Data team. You will design and maintain thousands of ingestion processes feeding investment decisions and operations, while building platforms that run and monitor these workflows across the firm.

The role emphasizes automation, reliability, and collaboration across international offices, with a fast-moving, delivery-focused environment and exposure to a range of data technologies.

Qualifications

• Experience building data ingestion pipelines and platforms.
• Ability to standardise ingestion methodologies and promote standards across teams.
• Strong automation mindset with track record of high-value automation opportunities.
• Ability to identify patterns and establish reliable development standards.
• Collaborative across geographies and teams to solve problems.

Responsibilities

• Build easily supportable data ingestion pipelines, platforms and systems.
• Explore data to identify features and issues and communicate them clearly across teams.
• Standardise ingestion methodologies and promote those standards to other teams via tools and libraries.
• Ensure systems are effective, scalable and flexible for growing business needs.
• Support, monitor and improve existing ingestion pipelines.

Skills

Automation

Collaboration

Problem-solving

Learning new tech

Delivery focus

Tools

Python

SQL

Pandas

Elasticsearch

Kibana

Snowflake

Docker

Kubernetes

Airflow

Spark

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, andcomplex 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.