Senior Data Engineer at NiX
Medellín, Antioquia, Colombia -
Full Time


Start Date

Immediate

Expiry Date

04 Jul, 25

Salary

0.0

Posted On

04 Apr, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Performance Tuning, Automation, Data Services, Data Engineering, Sql, Stored Procedures, Git, Glue, Data Warehousing, Python, Scripting, Advanced, Data Manipulation, Computer Science

Industry

Information Technology/IT

Description

N-iX is looking for a Senior Data Engineer in Medellin.
As a Data Engineer, you will dive into the heart of data infrastructure, crafting solutions that drive business forward. You will collaborate with a dynamic team to transform raw data into actionable insights.

REQUIREMENTS:

  • Bachelor’s degree in Computer Science, Engineering, or a related field
  • 5+ years of experience in data engineering, with a focus on SQL, and data warehousing
  • Solid understanding of data warehousing concepts and best practices
  • Strong proficiency in SQL, with experience in writing complex queries, stored procedures, and performance tuning
  • Nice to have proficiency in Python for data manipulation, scripting, and automation
  • Nice to have BI knowledge(SQL Server Reporting services, PowerBI)
  • Hands-on experience with AWS data services such as Redshift, Lambda, Glue, S3, etc.
  • Experience with version control systems such as Git
  • Strong analytical and problem-solving skills with attention to detail
  • Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment
  • Upper-Intermediate or Advanced English Level
Responsibilities
  • Design, develop, and maintain scalable data pipelines and ETL processes in AWS environment
  • Architect and implement efficient data warehousing solutions, ensuring optimal performance and reliability
  • Collaborate with data scientists and analysts to understand business requirements and translate them into technical solutions
  • Optimize and tune existing data pipelines and queries to improve performance and reduce latency
  • Ensure data integrity, quality, and security across all data processes and systems
  • Troubleshoot and resolve data-related issues in a timely manner
  • Stay updated with industry trends and best practices in data engineering, recommending, and implementing new technologies and methodologies as needed
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