Data Engineer

Luxoft; United States; Remote; USD 110,000 - 160,000; Full time

Job summary

Luxoft in the United States is seeking an autonomous Data Engineer to strengthen our data foundation for an energy solutions platform. You will design, model and optimize ingestion pipelines feeding the app and analytics, with Snowflake, AWS and modern tooling.

You will collaborate with product teams to define criteria, onboard client data via APIs and Databricks Delta Sharing, and build reliable, well-tested data layers ready for analytics and future AI use cases.

Qualifications

• End-to-end ownership of production data pipelines.
• Strong SQL and production Python development experience.
• Experience with cloud data warehouses and data modeling.
• Clear, effective communication in English.

Responsibilities

• Architect and maintain robust data ingestion pipelines powering app and analytics.
• Design well-modeled, layered tables with clean schemas for analytics.
• Onboard client data from sources like Databricks via Delta Sharing and integrate with services.
• Make pipelines reliable with data quality tests, monitoring and safe reprocessing.
• Build a documented data foundation for app, analytics and AI use cases.

Skills

End-to-end data pipelines

Autonomous IC

SQL

Python

Node.js/TypeScript

AWS / cloud platform

CI/CD

AI-native development

Data modeling / clean schemas

Communication skills

Tools

Airflow

Dagster

Step Functions

Snowflake

Databricks

Terraform

Job description

Project description

Our client is an energy solutions provider. Our AI-enabled platform supports operations, tracking and decision-making to optimize large-scale renewable and traditional energy portfolios. We're delivering a key client MVP in February 2027, and the project continues into 2028. Our stack: Ruby on Rails, Node.js/TypeScript and Python services, PostgreSQL, Snowflake and AWS. We're looking for an autonomous data engineer to strengthen our data foundation through good modeling, clean schemas, reliability and automation.

Responsibilities

• Work closely with product teams to help define and execute technical criteriaArchitect and maintain robust data ingestion pipelines that feed both our application and analyticsDesign well-modeled, layered tables with clean schemas that turn raw data into analytics-ready dataHelp onboard client data from a variety of sources, such as Databricks via Delta Sharing, and integrate it with our existing services and workflowsMake pipelines reliable and automated: data quality tests, monitoring, safe reprocessing and schema change handlingBuild a documented, well-tested data foundation that serves the app, analytics and future AI use cases

SKILLS

Must have

• Mid-to-senior data engineer who has owned the design of production data pipelines end to end, working as an autonomous ICDesigning and building production ingestion pipelines from APIs, files and shared-data sources, using a workflow orchestrator (any tool, e.g. Airflow, Dagster or Step Functions)Production experience with a cloud data warehouse (Snowflake preferred)Strong SQL, plus production experience in Python (preferred) or Node.js/TypeScriptAWS or another enterprise cloud platformAI-native development: daily use of agentic AI coding tools, and experience scaling shared AI workflows across a team and into the development lifecycle, including CI/CDStrong English and communication skills

Nice to have

• dbtPreparing data for AI/LLM use (e.g. semantic layers, metadata, retrieval-ready datasets)Infrastructure as code (e.g. Terraform)Exposure to energy, utilities or sustainability data