Senior Databricks Engineer [Python / SQL / DataBrick / Azure]

Luxoft Malaysia; Penang; On-site; MYR 120,000 - 180,000; Full time

Job summary

Luxoft Malaysia is seeking a versatile Data Solutions Engineer to support the complete data lifecycle—from ingestion and engineering to analytics, visualization, and API enablement. You will work closely with business stakeholders, develop reporting capabilities, and contribute across multiple data initiatives including data science and AI use cases.

The role rotates between Data Engineering, Data Analytics, and Data Visualization as priorities shift, requiring a flexible mindset and

Qualifications

• Proficient in Python, SQL and data processing frameworks.
• Experience with Databricks or Apache Spark (PySpark) is required.
• Ability to translate business needs into analytical data products.
• Experience building dashboards and APIs for data products.

Responsibilities

• Design, develop, and maintain scalable data pipelines.
• Build and optimize ETL/ELT processes.
• Develop data ingestion, transformation, and aggregation workflows.
• Ensure data quality, reliability, and performance.
• Develop solutions using cloud-based data platforms.
• Build and optimize data processing notebooks and workflows.
• Work with Data Lakes, Lakehouse architectures, and distributed data processing technologies.
• Support CI/CD and deployment activities for data solutions.
• Collaborate with business users to gather and clarify requirements.
• Translate business needs into analytical and technical solutions.
• Develop KPI calculations, reporting logic, and support data exploration for business insights.
• Build dashboards and reports to enable self-service analytics and decision‑making.
• Develop and maintain APIs to expose data products and integrate with consuming applications.

Skills

Python

SQL

Databricks

Spark

PySpark

FastAPI

REST API

Tools

Databricks

Spark

PySpark

Job description

• We are looking for a versatile Data Solutions Engineer capable of supporting the complete data lifecycle, from data ingestion and engineering to analytics, visualization, and API enablement.
• The ideal candidate combines strong Data Engineering fundamentals with the ability to work closely with business stakeholders, develop reporting solutions, and contribute across multiple data-related initiatives. Exposure to Data Science and AI use cases is considered an advantage.
• This role requires a flexible mindset, as the engineer may rotate between Data Engineering, Data Analytics, and Data Visualization initiatives depending on project priorities.

Responsibilities:

• Design, develop, and maintain scalable data pipelines.
• Build and optimize ETL/ELT processes.
• Develop data ingestion, transformation, and aggregation workflows.
• Ensure data quality, reliability, and performance.
• Develop solutions using cloud-based data platforms.
• Build and optimize data processing notebooks and workflows.
• Work with Data Lakes, Lakehouse architectures, and distributed data processing technologies.
• Support CI/CD and deployment activities for data solutions.
• Collaborate with business users to gather and clarify requirements.
• Translate business needs into analytical and technical solutions.
• Develop KPI calculations, reporting logic, and support data exploration for business insights.
• Build dashboards and reports to enable self-service analytics and decision‑making.
• Develop and maintain APIs to expose data products and integrate with consuming applications.

Mandatory Skills Description:

Programming:

• Python
• SQL
• Databricks or Apache Spark / PySpark

Examples:

Data Processing:

• ETL / ELT
• Data Modeling

APIs:

• FastAPI (preferred)
• Flask / REST API development experience acceptable