GCP Data Engineer

The GCP Data Engineer will be responsible for constructing and developing large-scale cloud data processing systems within the Google Cloud Platform (GCP). This role involves curating a comprehensive data set that includes information about users, groups, and their permissions to various data sets. The engineer will redesign and implement a scalable data pipeline to ensure timely updates and transparency in data access. REQUIRED SKILLS 5+ years of experience in an engineering role using Python, Java, Spark, and SQL. 5+ experience working as a Data Engineer in GCP Demonstrated proficiency with Google's Identity and Access Management (IAM) API Demonstrated proficiency with Airflow Key Responsibilities Design, develop, and implement scalable, high-performance data solutions on GCP. Ensure that changes to data access permissions are reflected in the Tableau dashboard within 24 hours. Collaborate with technical and business users to share and manage data sets across multiple projects. Utilize GCP tools and technologies to optimize data processing and storage. Re-architect the data pipeline that builds the BigQuery dataset used for GCP IAM dashboards to make it more scalable. Run and customize DLP scans. Build bidirectional integrations between GCP and Collibra. Explore and potentially implement Dataplex and custom format-preserving encryption for de-identifying data for developers in lower environments. Qualifications – Required Bachelor's degree in Computer Engineering or a related field. 5+ years of experience in an engineering role using Python, Java, Spark, and SQL. 5+ years of experience working as a Data Engineer in GCP. Proficiency with Google's Identity and Access Management (IAM) API. Strong Linux/Unix background and hands-on knowledge. Experience with big data technologies such as HDFS, Spark, Impala, and Hive. Experience with Shell scripting and bash. Experience with version control platforms like GitHub. Experience with unit testing code. Experience with development ecosystems including Jenkins, Artifactory, CI/CD, and Terraform. Demonstrated proficiency with Airflow. Ability to advise management on approaches to optimize for data platform success. Ability to effectively communicate highly technical information to various audiences, including management, the user community, and less-experienced staff. Proficiency in multiple programming languages, frameworks, domains, and tools. Coding skills in Scala. Experience with GCP platform development tools such as Pub/Sub, Cloud Storage, Bigtable, BigQuery, Dataflow, Dataproc, and Composer. Knowledge in Hadoop and cloud platforms and surrounding ecosystems. Experience with web services and APIs (RESTful and SOAP). Ability to document designs and concepts. API Orchestration and Choreography for consumer apps. Well-rounded technical expertise in Apache packages and hybrid cloud architectures. Pipeline creation and automation for data acquisition. Metadata extraction pipeline design and creation between raw and transformed datasets. Quality control metrics data collection on data acquisition pipelines. Experience contributing to and leveraging Jira and Confluence. Strong experience working with real-time streaming applications and batch-style large-scale distributed computing applications using tools like Spark, Kafka, Flume, Pub/Sub, and Airflow. Ability to work with different file formats like Avro, Parquet, and JSON. Hands-on experience in Analysis, Design, Coding, and Testing phases of the Software Development Life Cycle (SDLC) #J-18808-Ljbffr