Data Engineer

Luxoft; California; Hybrid; USD 140,000 - 200,000; Full time

Job summary

Luxoft is seeking an autonomous Data Engineer in California to strengthen our data foundation. You will own end-to-end data pipelines, design clean data models, and onboard diverse client data (e.g., Databricks via Delta Sharing) into Snowflake and our services.

The role demands strong SQL and Python skills, experience with workflow orchestration tools (Airflow/Dagster/Step Functions), and solid English communication to collaborate across product teams and AI initiatives.

Qualifications

• End-to-end ownership of production data pipelines as an autonomous IC.
• Production Snowflake data warehouse experience.
• Strong SQL and Python (or Node.js/TypeScript) production skills.
• Excellent English communication.

Responsibilities

• Architect and maintain robust data ingestion pipelines feeding 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 and automated with data quality tests and monitoring.
• Build a documented, well-tested data foundation for app, analytics, and AI use cases.

Skills

Data pipelines

Snowflake

SQL

Python

Airflow

CI/CD

English

Tools

Databricks

Delta Sharing

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