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Data/AI engineer with Python

Technology
Luxoft
1 tydzień temuDo 24.12.2026
Pełny etatStacjonarna

Opis stanowiska

Who are we

DXC Luxoft is a global IT services and consulting company, part of DXC Technology, delivering cutting-edge digital and software solutions worldwide. We partner with leading financial institutions and global enterprises, helping them transform and scale through modern technology.

Join a global community of engineers and be part of building impactful, modern technology solutions!

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.

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.
  • Experience operating in agile delivery environments.
  • Strong communication skills and ability to interact efficiently with various stakeholder groups including business users.
Nice-to-Have Skills Description:
  • 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.

Languages:

English: B2 Upper Intermediate

Keywords
PythonData EngineeringData PipelinesData IntegrationAI/LLM ApplicationsLangGraphLangChainAgentic WorkflowsRelational DatabasesGraph DatabasesVector DatabasesAnalytical Data PlatformsAWSInfrastructure as CodeSparkDatabricksData QualityData LineageData MonitoringAI

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