Data Engineer - 1010

Major Responsibilities

• Data Transformation: Collect, manage, and transform large-scale raw data from multiple sources into structured, reliable, and usable formats that meet business and analytical requirements.
• Data Tool Creation: Design, develop, and maintain data architectures, pipelines, and applications using appropriate tools and frameworks to support scalable data processing and product development.
• ETL Development: Build and maintain robust extract, transform, and load (ETL) processes that ensure data accuracy, efficiency, and availability across systems.
• Root Cause Analysis & Continuous Improvement: Perform root cause analysis to identify data issues, system inefficiencies, or process gaps, and implement improvements that enhance data quality and operational performance.
• Agile Collaboration: Work in an agile Scrum environment by contributing to sprint planning, development tasks, testing, and sprint reviews to deliver reliable and scalable data solutions.

Education and Experience

• Bachelor’s in Computer Science, Mathematics, Statistics, or related field (or equivalent experience)
• 2+ years in data engineering, data analysis, or similar roles
• Experience with ETL, data warehousing, and scalable data systems
• Solid understanding of statistical methods and data analysis
• Strong communication skills with ability to work independently and in teams
• Proficiency in Python and SQL; familiarity with Java, C/C++, or similar
• Strong software engineering, programming, and QA skills
• Experience with Linux/Unix (POSIX systems) and Git

Preferred Qualifications

• Experience with Docker, Terraform, and AWS (Batch, EMR/Spark, ecosystem tools)
• Familiarity with GitLab and Scala