Data Engineer

2 days ago

Batam Riau Islands, Indonesia Glints Full time

Role Overview

We are looking for a Data Engineer to design, build, and maintain our data infrastructure and pipelines. You will work closely with the Product and Engineering teams to ensure data is accessible, reliable, and optimised for analytics and business intelligence. Additionally, you will partner with the leadership team to identify business opportunities through data-driven insights.

Responsibilities

  • Design and implement scalable data pipelines and ETL processes
  • Build and maintain data warehouses and data lakes
  • Optimise data storage and retrieval for performance and cost-efficiency
  • Collaborate with Product and Engineering teams to understand data requirements
  • Partner with leadership to uncover business opportunities through data analysis and insights
  • Ensure data quality, integrity, and security across all systems
  • Monitor and troubleshoot data pipeline issues
  • Manage and improve data dependencies across systems and workflows
  • Develop and maintain documentation for data architecture and processes

Requirements

  • Strong experience with SQL and database technologies (PostgreSQL, MySQL, SQL Server, etc.)
  • Knowledge of on-premises database management and optimisation
  • Familiarity with C# and .NET Core backend development
  • Experience with SQL Server and IIS hosting environments
  • Proficiency in Python
  • Experience with cloud platforms like Azure
  • Knowledge of data pipeline tools
  • Experience with version control (Git) and CI/CD practices
  • Knowledge of containerisation and orchestration (Docker, Kubernetes)
  • Familiarity with data visualisation tools (Tableau, Power BI, Metabase)
  • Understanding of machine learning workflows and MLOps
  • Experience building AI tools and data query solutions for business stakeholders
  • Strong problem-solving and analytical thinking
  • Excellent communication and collaboration skills
  • Ability to work independently and manage priorities
  • Attention to detail and commitment to data quality

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