Responsibilities:

• Design, build, and maintain scalable data pipelines (ETL - Extract, Transform, Load) from various sources (structured and unstructured databases) using Airbyte and Airflow.
• Optimize PostgreSQL and Google BigQuery to enhance data processing performance and reliability.
• Maintain dataflows from MongoDB to Google BigQuery.
• Develop dashboards and reports in Apache Superset to enable data visualization and decision-making based on interactions with other departments.
• Ensure data quality, security, and accessibility by collaborating with cross-functional teams.

Requirements:

• Bachelor's or Master's degree in Computer Science, Data Engineering, Mathematics, Physics or a related field. Equivalent experience in place of a degree is applicable.
• Minimum 2 years of experience in data engineering or related fields.

Core Tech Stack:

• PostgreSQL, Google BigQuery for database management.
• Airbyte, Airflow for data pipeline automation.
• Apache Superset for visualization and reporting.
• Git based code revision control system.

Cloud Proficiency: Experience with Google Cloud Platform (GCP) for data processing and storage.

Programming Skills:

• Advanced SQL for efficient data transformation.
• Working knowledge of Python for scripting and automation.
• Basic JavaScript for BigQuery Dataform functions where applicable.
• Strong problem-solving skills with the ability to work independently.
• Fluency in spoken English communication for effective collaboration across teams.