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Data/AI engineer with Python
Luxoft
1 hour ago
Full-time
On-site
Los Angeles, California, United States
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, with a latency and cost in mind
Experience working with relational databases and modern data storage technologies, including graph, vector, or analytical data platforms.
Experience with data quality and data governance approaches, including validations in the pipeline, entitlements, audit, and lineage
Experience operating in agile delivery environments.
Strong communication skills and ability to interact efficiently with various stakeholder groups including business users.AI Acumen
Experience applying modern agentic approaches (spec-driven development) to software engineering
Hands-on with Claude Code, VS Code + Copilot, and building or using reusable Al skills
Al-first repositories
build agent-ready repos
context, skills, conventions & evals baked in
Quality
agent-generated test & regression suites; identify and guide agents to build quality unit and system test cases
Nice to have
Highly desirable: financial services, specifically fixed income or trading domains experience
Experience with Databricks, Spark, Delta Lake, or similar modern data engineering platforms.
Experience designing enterprise data lakes, lakehouses, or large-scale analytical platforms.
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.
Other
Languages
English: B2 Upper Intermediate
Seniority
Senior
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, with a latency and cost in mind
Experience working with relational databases and modern data storage technologies, including graph, vector, or analytical data platforms.
Experience with data quality and data governance approaches, including validations in the pipeline, entitlements, audit, and lineage
Experience operating in agile delivery environments.
Strong communication skills and ability to interact efficiently with various stakeholder groups including business users.AI Acumen
Experience applying modern agentic approaches (spec-driven development) to software engineering
Hands-on with Claude Code, VS Code + Copilot, and building or using reusable Al skills
Al-first repositories
build agent-ready repos
context, skills, conventions & evals baked in
Quality
agent-generated test & regression suites; identify and guide agents to build quality unit and system test cases
Nice to have
Highly desirable: financial services, specifically fixed income or trading domains experience
Experience with Databricks, Spark, Delta Lake, or similar modern data engineering platforms.
Experience designing enterprise data lakes, lakehouses, or large-scale analytical platforms.
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.
Other
Languages
English: B2 Upper Intermediate
Seniority
Senior