Senior Data Backend Engineer (Python, Databricks, Azure)

Luxoft; Malaysia; On-site; MYR 180,000 - 280,000; Full time

Job summary

Luxoft is seeking a Senior Data Engineer for a premium German OEM across Asia. You will build scalable data processing pipelines in Python/Databricks, expose analytics via REST APIs, and optimize data models on Azure cloud. You will mentor juniors and influence architectural decisions.

You will collaborate with analysts and product teams to translate requirements into robust data solutions, ensuring high performance, monitoring, and scalable data architecture across the region.

Qualifications

• 5+ years of software/data engineering experience
• Hands-on experience with Databricks
• Strong SQL and data modeling skills
• Experience developing APIs with Fast API
• Experience with Azure cloud services
• Understanding of ETL/ELT concepts and data pipeline design
• Experience with Git and CI/CD pipelines

Responsibilities

• Design and develop scalable data processing solutions using Python and Databricks
• Build and maintain data pipelines for ingestion, transformation, and aggregation of business data
• Develop REST APIs using FastAPI to expose data and analytical services to consuming applications
• Design and optimize SQL queries and data models
• Collaborate with business analysts, data engineers, and product stakeholders to translate business requirements into technical solutions
• Deploy and maintain solutions on Microsoft Azure
• Drive best practices in performance optimization, monitoring, testing, and code quality
• Mentor junior engineers and contribute to architectural decisions

Skills

Python

FastAPI

SQL

APIs design

CI/CD

Git

Azure

ETL/ELT

Tools

Databricks

Job description

Luxoft is seeking a Senior Data Engineer for a premium German OEM across Asia. You will build scalable data processing pipelines in Python/Databricks, expose analytics via REST APIs, and optimize data models on Azure cloud. You will mentor juniors and influence architectural decisions.

You will collaborate with analysts and product teams to translate requirements into robust data solutions, ensuring high performance, monitoring, and scalable data architecture across the region.