Data/AI engineer with Python

Luxoft Poland; Polska; On-site; PLN 240,000 - 360,000; Full time

Benefits offered by this job

Private medical insurance

Dental care

Life insurance

MyBenefit program

Job summary

Luxoft Poland is seeking a senior data engineer to build reusable platform capabilities and data products for quantitative researchers across a complex data landscape. You will design, build, and enhance data pipelines and integration frameworks to support AI, analytics, and business applications.

The role requires 10+ years in software development with 5+ years in data engineering, proficiency in Python, and hands-on experience with Databricks, Spark, Delta Lake, and AWS data services.

Qualifications

• 10+ years of professional software development, including 5+ years of data engineering experience.
• Advanced proficiency in Python, including experience building scalable backend services and data processing solutions.
• Strong hands-on experience designing and implementing data pipelines, data integration solutions, and large-scale data processing architectures.
• Experience with relational databases and modern data storage technologies, including graph, vector, or analytical data platforms.
• Practical experience building and deploying AI/LLM-enabled applications in production environments.
• Experience with LangGraph, LangChain, agentic workflows, or orchestration frameworks for AI applications; evaluations.
• Familiarity with modern AI tooling and workflows, including AI-assisted software engineering practices.
• Strong communication skills and ability to interact efficiently with various stakeholder groups including business users.
• Experience with Databricks, Spark, Delta Lake, or similar modern data engineering platforms.
• Experience designing enterprise data lakes, lakehouses, or large-scale analytical platforms.
• Domain experience within Investment Management, Asset Management, Capital Markets, or Financial Services.
• Strong understanding of Fixed Income products and related investment workflows.
• Experience with Aurora, Neptune, and other AWS data services.
• Strong hands-on experience designing and implementing data pipelines, data integration solutions, and large-scale data processing architectures.
• Experience architecting, provisioning, and managing production infrastructure on AWS, including services such as ECS Fargate, Lambda, SQS, and related cloud-native technologies.
• Experience defining cloud architecture programmatically using Infrastructure-as-Code (IaC) tools such as AWS CDK or Terraform.

Responsibilities

• Design, build, and enhance data pipelines and integration frameworks supporting AI, analytics, and business applications.
• Improve data quality, reliability, lineage, and monitoring.
• Implement AI first approach: use AI agents as a primary tool to design, build, test, and support solutions
• Collaborate closely with business stakeholders, product managers, and engineering teams to translate business objectives into technical solutions.

Skills

Software development

Data engineering

Python

Data pipelines

AI/LLM tooling

AWS data services

LangGraph/LangChain

Communication with stakeholders

Tools

Databricks

Spark

Delta Lake

AWS (ECS Fargate, Lambda, SQS)

Job description

Private Medical & Dental care & Life Insurance (covered by us on Employment contract)

MyBenefit program (sports card, well-being program etc.) (covered by us on Employment contract)

Internal Mobility program - possibility of rotation between projects, locations, accounts

… and many more!

Build reusable platform capabilities and data products that let quantitative researchers discover, access, and consume data across a complex, disparate landscape, and then accelerate the good prototypes to production.

• Design, build, and enhance data pipelines and integration frameworks supporting AI, analytics, and business applications.
• Improve data quality, reliability, lineage, and monitoring.
• Implement AI first approach: use AI agents as a primary tool to design, build, test, and support solutions
• Collaborate closely with business stakeholders, product managers, and engineering teams to translate business objectives into technical solutions.

Mandatory Skills Description:

• 10+ years of professional software development, including 5+ years of data engineering experience.
• Advanced proficiency in Python, including experience building scalable backend services and data processing solutions.
• Strong hands-on experience designing and implementing data pipelines, data integration solutions, and large-scale data processing architectures
• Experience working with relational databases and modern data storage technologies, including graph, vector, or analytical data platforms.
• Practical experience building and deploying AI/LLM-enabled applications in production environments.
• Experience with LangGraph, LangChain, agentic workflows, or orchestration frameworks for AI applications; evaluations.
• Familiarity with modern AI tooling and workflows, including and AI-assisted software engineering practices.
• Strong communication skills and ability to interact efficiently with various stakeholder groups including business users.
• Experience with Databricks, Spark, Delta Lake, or similar modern data engineering platforms.
• Experience designing enterprise data lakes, lakehouses, or large-scale analytical platforms.
• Domain experience within Investment Management, Asset Management, Capital Markets, or Financial Services.
• Strong understanding of Fixed Income products and related investment workflows. Candidates with significant Fixed Income domain expertise will be considered highly valuable.
• Experience with Aurora, Neptune, and other AWS data services.
• Strong hands-on experience designing and implementing data pipelines, data integration solutions, and large-scale data processing architectures.
• Experience architecting, provisioning, and managing production infrastructure on AWS, including services such as ECS Fargate, Lambda, SQS, and related cloud-native technologies.
• Experience defining cloud architecture programmatically using Infrastructure-as-Code (IaC) tools such as AWS CDK or Terraform.