Senior Analytics Engineer: Azure Lakehouse & BI (Hybrid)

Randstad Malaysia; Kuala Lumpur; Hybrid; MYR 180,000 - 240,000; Full time

Benefits offered by this job

Public Transport Access

Hybrid Working (3+2)

Financial Services Industry

Job summary

Randstad Malaysia is seeking a seasoned Data/Analytics Engineer to design and operate data pipelines using Azure PaaS, build lakehouse architectures, and deliver Power BI dashboards for a financial services client.

You will transform raw data into dimensional models, optimize queries with SQL, Python, and PySpark, and contribute to modern data platform developments in a hybrid work setup.

Qualifications

• 6+ years of proven experience in Data Engineering, Analytics Engineering, or Business Intelligence.
• Hands-on with Azure PaaS data tools (ADF, ADLS Gen2, Databricks, Azure SQL).
• Experience with Azure Fabric (Data Engineering and Power BI workloads).
• Expertise in Power BI, including advanced DAX, Power Query, and tabular modeling.
• Strong SQL and Python (or PySpark).
• Understanding of dimensional modeling and modern lakehouse architecture.

Responsibilities

• Data Engineering: Build and manage ETL/ELT data pipelines using Azure PaaS (e.g., ADF, Databricks).
• Lakehouse Architecture: Implement and manage our Data Lakehouse with Azure Fabric (OneLake).
• Data Modeling: Transform raw data into clean, structured dimensional models (Star Schema).
• Analytics & BI: Design and develop reports and dashboards using Power BI.
• Code & Optimization: Write advanced SQL queries, DAX measures, and Python/PySpark scripts to transform data and optimize query performance.

Skills

SQL

Python

PySpark

DAX

Power BI

Data Modeling

Dimensional Modeling

Lakehouse Architecture

Star Schema

Azure Fabric

Azure PaaS

Databricks

Azure Data Factory

Power Query

Education

Associate Degree/Diploma

Tools

Azure Data Factory

Azure Data Lake Storage Gen2

Databricks

Azure SQL

Power BI

Job description

Randstad Malaysia is seeking a seasoned Data/Analytics Engineer to design and operate data pipelines using Azure PaaS, build lakehouse architectures, and deliver Power BI dashboards for a financial services client.

You will transform raw data into dimensional models, optimize queries with SQL, Python, and PySpark, and contribute to modern data platform developments in a hybrid work setup.