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About the role
Bachelors Degree in Engineering, Computer Science, CIS, or related field (or equivalent work experience in a related field) 2 years of experience in Data, Platform Engineering, Data Warehousing/ETL, Cloud Platform or Software Engineering 1 year of experience working on project(s) involving the implementation of solutions applying development life cycles (SDLC) Preferred Qualifications Masters Degree in Computer Science, CIS, or a related field 2 years of IT experience in developing and implementing business systems within an organization 4 years of experience with technical documentation in a software development environment 2 years of experience with Big Data technologies - both On-Premises and Cloud 2 years of experience with Hadoop and Spark Experience with application and integration middleware Experience with database technologies Data Engineering 2 years of experience with Hadoop or any Cloud Big Data components (specific to the Data Engineering role), preferably Google Cloud Platform Expertise in Java/Scala/Python, SQL, Scripting, Hadoop (Sqoop, Hive, HDFS), Spark (Spark Core Streaming), Kafka or equivalent Cloud Big Data components Proficiency in programming languages: Scala, Python, Java, and Big Data technologies, both On-Premises and Cloud Knowledge of data modeling and database design Hands-on experience with GCP services: BigQuery, Dataflow, Dataproc, Composer/Airflow, Google Storage, Pub-Sub Experience with CI/CD processes: Jenkins, Cloud build tools, Docker, Kubernetes, Artifact Registry Ability to design scalable data architectures on GCP using services like Dataproc, BigQuery, and Composer Experience with ETL (Extract, Transform, Load) processes Responsible for optimizing data pipelines and queries for performance, troubleshooting issues, and proactive monitoring Knowledge of quality checks, data governance, and security policies
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