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