GCP Lead or Architect

Client is seeking a Senior Big Data Engineer to become part of the team implementing and supporting edge analytical solutions on a Google Cloud Ecosystem. You will find a great place to work if you are passionate about designing data ingestion jobs, learning new technologies, and proposing and adopting new technologies. What you'll do

• Extract, Transform and Load data from multiple sources and multiple formats using Big Data Technologies.
• Development, enhancement, and support of data ingestion jobs from various source systems following existing design patterns using GCP Services such as Apache Spark, Dataproc, Dataflow, BigQuery, Airflow, etc.
• Work across Teams and senior engineers to make Data more accessible to others within the organization.
• Modify data extraction pipelines into standardized approaches that can be repeatable and reusable with minimal supervision from senior engineers.
• Automation of manual processes, optimize data delivery, re-designing infrastructure for greater scalability, etc.
• Work closely with senior engineers to optimize query and data access techniques.
• Apply modern software development practices (serverless computing, microservices architecture, CI / CD, infrastructure-as-code, etc.)
• Participate in a tight-knit engineering team employing agile software development practices. What experience you need
• Bachelor's degree in Computer Science, Systems Engineering or equivalent experience.
• 5+ years of work experience as a Big Data Engineer.
• 3+ years of experience using Technologies such as Apache Spark, Hive, HDFS, Beam (Optional).
• 3+ years of experience in SQL and Scala or Python.
• 2+ years experience with software build management tools like Maven or Gradle.
• 2+ years of experience working with Cloud Technologies such as GCP, AWS or Azure.
• What could set you apart
• Data Engineering using GCP Technologies (BigQuery, DataProc, Dataflow, Composer, DataStream, etc)
• Experience writing data pipelines.
• Self-starter that identifies / responds to priority shifts with minimal supervision
• Source code control management systems (e.g. SVN / Git, Github) and build tools like Maven & Gradle.
• Agile environments (e.g. Scrum, XP)
• Relational databases (e.g. SQL Server, Oracle, MySQL)
• Atlassian tooling (e.g. JIRA, Confluence, and Github