Roles & Responsibilities:

Provide support and guidance to other Data Engineers.
Manage the analytics data warehouse, implementing analytical database design principles and business process best practices.
Design, develop, and maintain scalable data pipelines using Apache Airflow.
Integrate and manage data within Google BigQuery to meet analytics and reporting needs.
Collaborate with cross-functional teams to understand data requirements and translate them into technical solutions.
Implement ETL processes to ensure efficient data extraction, transformation, and loading from multiple sources.
Optimize data workflows while ensuring data quality, consistency, and security.
Monitor and troubleshoot performance and reliability of data pipelines.
Stay current with trends and new technologies in data engineering and cloud platforms.
Identify, design, and implement internal process improvements such as automation, data delivery optimization, and infrastructure redesign for greater scalability.
Support analytical requests cross-functionally for internal and external stakeholders.

Skill Set Required:

Must have:

Experience developing solutions on cloud computing platforms, with GCP experience preferred.
5+ years hands-on development experience with frameworks such as Python, Java, or Scala.
Proficiency in Python; Google BigQuery, Google Storage, Cloud Composer, Dataflow; Google PubSub; SQL; Ansible; Tableau APIs; Jenkins; and Shell scripting.

Nice to have:

Experience with Data Warehouse and ETL migrations.
Advanced SQL knowledge and experience authoring complex queries in relational databases.
Experience with Scala, Python, PySpark, Java, REST API, Microservices, etc.
Prior experience implementing real-time streaming data solutions into an Enterprise Data Warehouse.
Experience in restaurant or retail operations preferred but not mandatory.

Senior Data Engineer