Data Engineer, Investment Services

Point72; Warszawa; On-site; PLN 70,000 - 90,000; Full time

Benefits offered by this job

Private medical and dental care

Private pension scheme

Educational assistance reimbursement

Sports card

Employee assistance program

Job summary

Dormont Manufacturing Co is looking for an AI/ML Data Engineer to join our Investment Services team in Warsaw, Poland. This full-time position involves architecting and maintaining high-throughput data pipelines while collaborating across teams to drive technological innovation.

You will be responsible for managing large volumes of data and ensuring data quality, adhering to the highest ethical standards. We provide competitive benefits including private medical care and educational reimbursement.

Qualifications

• 3+ years of experience in data engineering or related field.
• Strong experience in Python development.
• Proficiency in building scalable, distributed data pipelines in a cloud environment.

Responsibilities

• Architect, develop, and maintain high-throughput data pipelines.
• Collaborate with AI Engineers and ML scientists to translate requirements.
• Optimize pipeline performance leveraging distributed processing techniques.

Skills

Python development

Data engineering

Data governance

Cloud environments

Data architecture

Spark or Scala

Education

Bachelor's or master's degree in computer science or engineering

Job description

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

• Architect, develop, and maintain high‑throughput data pipelines in Databricks and AWS (Glue, EMR, Fargate, Step Functions)
• Ingest, normalize, and enrich large volumes of structured and unstructured data including internal data, market data, third‑party/vendor feeds, document repositories, and alternative data sources
• Collaborate with AI Engineers, ML scientists, and software engineers to translate model and product requirements into scalable data architecture, schemas, and APIs
• Optimize pipeline performance (compute, storage, network) and cost by leveraging distributed processing techniques (Spark, Delta, Arrow) and AWS best practices (spot fleets, autoscaling)
• Enforce data governance, privacy, and lineage standards, cataloging assets in Unity Catalog, managing PII/PCI classification, and implementing fine‑grained access controls with Immuta/Ranger/IAM
• Build automated validation, testing, and monitoring frameworks to guarantee data quality, freshness, and drift detection for both offline and online workloads
• Support the onboarding and integration of new external data vendors, ensuring contractual compliance, metadata management, and rapid time‑to‑value for relevant teams
• Continuously evaluate emerging GenAI tooling (vector stores, LLMOps platforms, synthetic‑data generators) and drive proof‑of‑concepts that enhance our data engineering capabilities

What’s Required

• Bachelor’s or master’s degree in computer science or engineering
• 3+ years of experience in data engineering or related field
• Strong experience in Python development
• Experience with Spark or Scala
• Proficiency in building scalable, distributed data pipelines in a cloud environment
• Solid understanding of data architecture principles, data modeling, and data warehousing
• Ability to devise novel and innovative solutions to challenges
• Knowledge of/experience with graph databases is a plus
• Commitment to the highest ethical standards

We take care of our people

We invest in our people, their careers, their health, and their well‑being. We want you to concentrate on success and leave the rest to us. When you work here, we provide:

• Sports card
• Private life insurance
• Private medical and dental care, with vision allowance
• Private pension scheme
• Volunteer opportunities
• Support for employee‑led affinity groups representing women, people of color and the LGBTQ+ community
• Business travel accident insurance
• Employee assistance program
• Educational assistance reimbursement