Data Engineer (GCP) (Mid to Senior)

• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and GCP ‘big data’ technologies.
• Create and maintain optimal data pipeline architecture.
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centers and GCP regions.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.

Qualifications:

• Bachelor's degree or higher - in Computer Science, Statistics, Informatics, Information Systems or another quantitative field
• 2+ years of experience in Data Engineer role (Junior - Mid Level)
• 5+ years of experience in Data Engineer role (Mid - Senior Level)
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Firestore.
• Experience with data pipeline and workflow management tools: Airflow, etc.
• Experience with GCP cloud services: Compute Engine, Cloud Function, Cloud Dataproc, Cloud SQL, BigQuery
• Experience with stream-processing systems: GCP Cloud Composer is a plus
• Experience with object-oriented/object function scripting languages: Python, Java, etc.
• Advanced SQL expertise with relational databases and query optimization
• Proven experience designing and optimizing large-scale “big data” pipelines, architectures, and datasets
• Track record of root-cause analysis on internal and external data to answer business questions
• Demonstrated success manipulating and extracting value from large, disconnected datasets
• Experience partnering with cross-functional teams in fast-paced environments
• Strong project management and organizational capabilities