Senior Data/AI engineer

Luxoft; Polska; Presencial; PLN 240.000 - 360.000; Jornada completa

Descripción de la vacante

Luxoft in Poland seeks a senior data engineer to design and scale data pipelines and platforms that empower quantitative researchers to discover, access, and use data across a diverse landscape. You will build reusable capabilities and data products, accelerating prototypes to production.

You will lead AI-first workflows, collaborate with stakeholders, and drive data quality, lineage, and monitoring while applying modern data technologies and cloud infrastructure.

Formación

• 10+ years of professional software development with 5+ years data engineering.
• Advanced Python proficiency with scalable backend services and data processing.
• Experience designing data pipelines, integration solutions, and large-scale processing.
• Relational databases and modern data storage platforms including graph, vector, analytics.
• Practical AI/LLM-enabled applications in production environments.
• LangGraph, LangChain, agentic workflows, or orchestration frameworks for AI apps.
• Familiarity with AI tooling and AI-assisted software engineering practices.
• Experience operating in agile delivery environments.
• Strong communication with business users and stakeholders.

Responsabilidades

• Design, build, and enhance data pipelines and integration frameworks for AI, analytics, and business apps.
• Improve data quality, reliability, lineage, and monitoring.
• Implement AI-first approaches using AI agents to design, build, test, and support solutions.
• Collaborate with business stakeholders, product managers, and engineering teams to translate objectives into technical solutions.

Conocimientos

10+ yrs exp

5+ yrs data engineering

Python backend

Data pipelines

Databases & analytics

AI in production

LangChain & AI workflows

AI tooling

Agile

Communication

Herramientas

Databricks

Spark

Delta Lake

AWS ECS Fargate

AWS Lambda

AWS SQS

AWS CDK / Terraform

Descripción del empleo

Project description

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.

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

Must have

• 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.
• Experience operating in agile delivery environments.
• Strong communication skills and ability to interact efficiently with various stakeholder groups including business users.

Nice to have

• 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.