Job Description

Responsibilities

• Design, develop, and maintain ETL (Extract, Transform, Load) pipelines to ensure reliable and efficient data flow for high-scale data flows.
• Manage and optimize data storage and retrieval in Google BigQuery, ensuring performance efficiency and cost-effectiveness.
• Setup quick analytics dashboards using tools like Metabase, Looker or any other.
• Collaborate with internal analysts and stakeholders, including customers, to understand data needs and implement robust solutions.
• Monitor, troubleshoot, and resolve data pipeline issues to ensure data integrity and availability.
• Implement data quality checks and maintain data governance standards across the ETL processes.
• Develop automation scripts for repetitive tasks and optimize manual processes.
• Document entire analytics implementation and data structures that can act as a guide for all users.
• Stay up-to-date with industry best practices and emerging technologies in data engineering and cloud-based data management.
• Provide guidance and mentorship to junior data engineers and data analysts as needed.

Requirements

• 4+ years of experience as a Data Engineer or in a similar role
• Strong experience with ETL tools and frameworks (e. g., Apache Airflow, Dataflow, Estuary).
• Proficiency in SQL and extensive experience with Google BigQuery.
• Experience in setting up analytics dashboards with various tools (Eg Looker, Metabase).
• Knowledge of data warehousing concepts and best practices.
• Experience with cloud platforms, particularly Google Cloud Platform (GCP).
• Strong analytical and problem-solving skills with a focus on cost optimization in cloud environments.
• Familiarity with Python or other scripting languages for automation and data processing.
• Excellent communication skills and the ability to work collaboratively in a team environment.
• Experience with data modeling and schema design.