Data Engineer

Role Overview

We are seeking a skilled Data Engineer to join our team and help build scalable, reliable, and high-performance data solutions. In this role, you will design and maintain production-grade data pipelines, develop ETL frameworks, and create governed datasets that support analytics and business decision-making. You'll collaborate closely with Analytics, Data Science, DevOps, and Engineering teams to deliver robust data platforms.

Responsibilities

• Design, build, and maintain scalable, production-grade data pipelines.
• Develop and maintain foundational data tables for business reporting and analytics.
• Build and optimize self-service ETL frameworks for batch and streaming data.
• Migrate, validate, and optimize data assets while ensuring data accuracy and quality.
• Integrate schema registries into ETL workflows and establish end-to-end data lineage.
• Monitor pipeline performance and implement data governance and quality standards.
• Collaborate with cross-functional teams to deliver scalable and reliable data solutions.
• Participate in code reviews, CI/CD deployments, and continuous improvement initiatives.

Requirements

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 4+ years of professional experience as a Data Engineer.
• Strong experience building production-grade data pipelines and transforming data into analytics-ready datasets.
• Proficiency in SQL, Python, Apache Spark (PySpark), and AWS Glue.
• Hands-on experience with Snowflake, Amazon Redshift, or Teradata.
• Strong understanding of data governance, data lineage, data quality, and pipeline monitoring.
• Experience with CI/CD processes using GitHub or Bitbucket.
• Experience working in Agile environments using JIRA and Kanban.

Skills

• Python
• SQL
• Apache Spark
• AWS Glue
• Snowflake