Data Engineer, Investment Services

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Offered From the posting source checked Jun 20, 2026

Relocation assistance

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Childcare support

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Learning budget

Offered From the posting source checked Jun 20, 2026

Verification

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Salary

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Data Engineer, Investment Services Warsaw A Career with Point72's AI/ML - Investment Services Team The AI/ML - Investment Services team at Point72 spearheads the development of cutting-edge AI solutions that seek to transform our business processes and enhance enterprise intelligence. The team aims to bridge the gap between business challenges and technological innovation, collaborating with stakeholders across the firm and leveraging expertise in generative AI, data engineering, and machine learning. WHAT YOU'LL DO - Design and build scalable, high-performance backend systems that power investment services and AI-driven applications, and own their end-to-end lifecycle - Build and operate robust data pipelines for batch and streaming workloads to ingest, transform, validate, and deliver data to models and downstream consumers - Integrate and productionize generative AI capabilities and large language model solutions, including model serving, embeddings, and API-based workflows to augment investment workflows - Implement and maintain microservices and APIs that expose data and model functionality with a focus on reliability, low latency, and security - Optimize system performance and resilience through monitoring, observability, capacity planning, and automated incident response - Lead cross-functional delivery of prototypes into production by collaborating with data scientists, researchers, product owners, and operations teams - Build and maintain CI/CD pipelines, automated testing, and deployment practices to accelerate safe delivery and rollback of services - Mentor and coach engineers on backend and data engineering best practices, help grow engineering capability, and contribute to the technical roadmap - Collaborate with security, compliance, and infrastructure partners to ensure data governance, access

Read the full description at boards.greenhouse.io. FewerJobs shows a preview and links to the original posting.