Data Engineer (C#/.NET Experience)

Programmers.io; Redmond; Presencial; AUD 140.000 - 180.000; Jornada completa

Descripción de la vacante

Programmers.io is seeking a data-focused engineer to integrate data from diverse sources, ensure quality and consistency, and troubleshoot data-related issues. You will design and maintain ETL pipelines, enabling real-time access to analytics data across systems.

The role emphasizes Python/C# development, SQL/Cosmos database experience, and building PowerBI dashboards to support data-driven decisions.

Formación

• Bachelor's degree in computer science or related engineering field.
• 5+ years of Python or C# experience.
• 5+ years of experience with database systems (SQL, Cosmos).
• 2+ years of experience with ETL and log analysis systems (SQL, Kusto, Application Insights, Grafana).
• 3+ years’ experience creating and maintaining PowerBI dashboards.

Responsabilidades

• Integrate data from APIs, data lakes, and third-party apps.
• Ensure data quality through validation checks and automated testing.
• Identify and troubleshoot data-related issues and propose improvements.
• Implement data pipelines that provide clean, real-time data for analytics.

Conocimientos

Python

C#

Analytical skills

Educación

Bachelor's degree in computer science or engineering

Herramientas

SQL

Cosmos DB

Kusto

Application Insights

Grafana

PowerBI

Azure Data Factory

ETL pipelines

Descripción del empleo

Bachelor's degree in computer science or other engineering disciplines.

5+ years of Python or C# experience.

5+ years of experience with database systems (SQL, Cosmos).

2+ years of experience with ETL (python, Azure Data foundry or similar) and log analysis systems (SQL, Kusto, Application Insights, Grafana, etc.).

3+ years’ experience creating and maintaining PowerBI dashboards.

Strong analytical skills - able to synthesize complex information and large datasets to drive decisions.

Responsibilities

• Integrate data from various internal and external sources such as APIs, data lakes, and third-party applications.
• Ensure the quality and consistency of data through the implementation of validation checks and automated testing.
• Identify and troubleshoot data-related issues, proposing solutions for improvements.
• Implement data pipelines that provide clean, accessible, and real-time data for analytical purposes.