Data Engineer

Requirements

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related technical field.
• Minimum 3 + years of hands-on experience in data engineering with strong expertise in data warehousing, pipeline development, and analytics on cloud platforms.
• Expert-level experience in: Google BigQuery for large-scale data warehousing and analytics.
• Python for data processing, orchestration, and scripting.
• SQL for data wrangling, transformation, and query optimization.
• DBT for developing modular and maintainable data transformation layers.
• Airflow / Cloud Composer for workflow orchestration and scheduling.
• Proven experience building enterprise-grade ETL/ELT pipelines and scalable data architectures.
• Strong understanding of data quality frameworks, validation techniques, and governance processes.
• Proficiency in Agile methodologies (Scrum/Kanban) and managing IT backlogs in a collaborative, iterative environment.
• Preferred experience with: Tools like Ascend.io , Databricks , Fivetran , or Dataflow .
• Data cataloging/governance tools (e.g., Collibra ).
• CI/CD tools, Git workflows, and infrastructure automation.
• Real-time/event-driven data processing using Pub/Sub , Kafka , or similar platforms.
• Strategic problem-solving skills and ability to architect innovative solutions.
• Ability to adapt quickly to new technologies and lead adoption across teams.
• Excellent communication skills and ability to influence cross-functional teams.
• Good experience on Agile Methodologies like Scrum, Kanban, and managing IT backlog.
• Be a "go-to" expert for data technologies and solutions.

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Company Intel

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