Data Platform Engineer – Hybrid (Securities/Data)

SMBC; New York (NY); Hybrid; USD 189,592 - 195,280; Full time

Benefits offered by this job

Hybrid work model

Annual discretionary incentive

Competitive benefits

Job summary

SMBC Group in the Americas seeks a data platform engineer to analyze, design, and develop the reference data system for securities and pricing data, collaborating with product managers and IT to meet business needs.

Hybrid remote work is permitted. Candidates should have a Master’s in Computer Science with 4 years of experience, including Python, APIs, Azure Databricks, Spark/Polars, and Bloomberg reference data.

Qualifications

• Master’s degree in computer science or related field with 4 years of experience.
• Experience must include Python programming, APIs, and reference data domains (Bloomberg, fixed income, equities).
• Familiarity with Azure Databricks, Spark, and Polars is required.

Responsibilities

• Analyze, design, and develop the data platform, starting with a reference data system for securities and pricing data.
• Collaborate with business teams, product managers, and stakeholders to translate requirements into applications.
• Engage with IT, security, and architecture to meet backend functionality and integration needs.
• Partner with UI/UX and front-end teams to align applications with the broader software ecosystem.
• Participate in regular development meetings to set priorities and share progress.

Skills

Python

APIs

Azure Databricks

Spark

Polars

Fixed income reference data

Equities reference data

Bloomberg reference data

Education

Master’s degree in computer science or related field

Job description

SMBC Group in the Americas seeks a data platform engineer to analyze, design, and develop the reference data system for securities and pricing data, collaborating with product managers and IT to meet business needs.

Hybrid remote work is permitted. Candidates should have a Master’s in Computer Science with 4 years of experience, including Python, APIs, Azure Databricks, Spark/Polars, and Bloomberg reference data.