🔎 Data/AI engineer with Python🔎

🟦 Join us in Luxoft!

(opportunity for PL based candidates )

💰 Paid Referrals

💻Equipment

🩺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

🎓 LuxTalent platform (webinars, training, courses)

… and many more!

🟦 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:

• 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: Upper Intermediate