Overview

A Data Engineer plays a crucial role in designing, building, and maintaining the infrastructure that powers our data-driven decisions. You’ll be at the heart of our data ecosystem, ensuring data is reliably collected, stored, and processed to provide clean, accessible data for our analytics and business intelligence teams.

Key Responsibilities

• Design & Develop Data Pipelines: Assist in building, maintaining, and optimizing scalable ETL/ELT data pipelines to ingest and transform large datasets from diverse sources, including APIs, databases, and third-party systems.
• Data Modeling & Warehousing: Support the development of robust data models and schemas in both relational and cloud-native data warehouses (e.g., Google BigQuery).
• Ensure Data Integrity: Monitor, troubleshoot, and improve the performance and reliability of data pipelines, ensuring data quality, consistency, and accuracy.
• Data Source Integration: Work with various data formats and sources, including structured, semi-structured, and streaming data.
• Data Governance & Security: Collaborate with senior engineers to enforce data governance, quality, and security standards across the organization.
• Code & Automation: Write clean, efficient, and well-documented code (SQL, Python) for data engineering tasks. Utilize Git and CI/CD principles for version control and automated deployments.
• Team Collaboration: Document data workflows and contribute to a shared knowledge base, providing ad-hoc support to data analysts and business users.

Required Skills & Experience

• Educational Background: Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• Professional Experience: 1-3 years of hands-on experience in a data engineering or similar role.
• Technical Proficiency:
• Communication & Soft Skills:
• Availability: Able to join immediately.