Senior Data Engineer - Azure Databricks, PySpark & Power BI

EXASOFT CONSULTING PTE. LTD.

Singapore

On-site

SGD 90,000 - 140,000

Full time

14 days+

Application generator

Turn this role into an interview — a resume and cover letter built around what this employer wants.

Get past ATS filters

Job summary

EXASOFT CONSULTING PTE. LTD. is seeking a data engineering professional to design and maintain robust data pipelines.

You will work with Azure Data Factory, Azure Databricks, PySpark, Python, and Delta Lake to deliver scalable analytics workflows. You will implement REST API integrations, ensure data quality with observability practices, and develop compelling Power BI dashboards for business insights. Collaboration with cross-functional teams and performance testing with JMeter are key parts of

Qualifications

Bachelor's or Master's degree in a technical field such as CS, Engineering or Data Science.
4+ years of professional experience in Data Engineering, Data Analytics, or related roles.
Strong hands-on experience with SQL and Azure Databricks for data processing and analytics.
Proficiency in PySpark, Python, and Azure Data Factory for workflows.
Experience with Azure DevOps, Delta Lake, REST API, JSON and Google BigQuery.
Experience building scalable data pipelines on cloud platforms.
Knowledge of data observability, monitoring and reliability practices.
Experience developing Power BI dashboards and reports.
Hands-on with JMeter for API/load testing and ETL processes.
Experience with anomaly detection and data quality practices.
Strong analytical, troubleshooting and collaboration skills.

Responsibilities

Develop reliable data pipelines for business and analytical use.
Utilize Azure Data Factory and Azure Databricks for ingestion, transformation, and processing workflows.
Write optimized SQL, Python, and PySpark for data prep.
Work with Delta Lake and Google BigQuery for analytical data storage.
Monitor data processes and apply observability practices.
Build REST API integrations for data exchange between apps.
Validate and process JSON data within data and API workflows.
Support automated builds and deployments via Azure DevOps.
Develop Power BI dashboards and reports for insights.
Conduct API/load/performance testing with JMeter.
Investigate issues and coordinate with teams to resolve data challenges.