Role : Google Cloud Platform Lead or Architect

Location-Atlanta, GA, Hybrid Onsite

lead or Architect

Mandatory Skills-Big Data, Google Cloud Platform, Apache Spark

JD-

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 Google Cloud Platform 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 Google Cloud Platform, AWS or Azure. What could set you apart Data Engineering using Google Cloud Platform 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