We are currently seeking a seasoned GCP Cloud Data Engineer with 3 to 5 years of experience in leading/implementing GCP data projects, preferrable implementing complete data centric model.This position is to design & deploy Data Centric Architecture in GCP for Materials Management platform which would get / give data from multiple applications modern & Legacy in Product Development, Manufacturing, Finance, Purchasing, N-Tier supply Chain, Supplier collaboration
- Requires a bachelor s or foreign equivalent degree in computer science, information technology or a technology related field
- 3 to 5 years of professional experience in:
- 3 years of cloud data/software engineering experience building scalable, reliable, and cost-effective production batch and streaming data pipelines using:
- Data engineering, data product development and software product launches
- At least three of the following languages: Java, Python, Spark, Scala, SQL and experience performance tuning.
- Data warehouses like Google BigQuery.
- Workflow orchestration tools like Airflow.
- Relational Database Management System like MySQL, PostgreSQL, and SQL Server.
- Real-Time data streaming platform like Apache Kafka, GCP Pub/Sub
- Microservices architecture to deliver large-scale real-time data processing application.
- REST APIs for compute, storage, operations, and security.
- DevOps tools such as Tekton, GitHub Actions, Git, GitHub, Terraform, Docker.
- Project management tools like Atlassian JIRA
Even better, you may have..
- Experience in IDOC processing, APIs and SAP data migration projects.
- Experience working in SAP S4 Hana environment
- You may not check every box, or your experience may look a little different from what weve outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
- Design and implement data-centric solutions on Google Cloud Platform (GCP) using various GCP tools like Storage Transfer Service, Cloud Data Fusion, Pub/Sub, Data flow, Cloud compression, Cloud scheduler, Gutil, FTP/SFTP, Dataproc, BigTable etc.
- Build ETL pipelines to ingest the data from heterogeneous sources into our system
- Develop data processing pipelines using programming languages like Java and Python to extract, transform, and load (ETL) data
- Create and maintain data models, ensuring efficient storage, retrieval, and analysis of large datasets
- Deploy and manage databases, both SQL and NoSQL, such as Bigtable, Firestore, or Cloud SQL, based on project requirements
- Collaborate with cross-functional teams to understand data requirements and design scalable solutions that meet business needs.
- Implement security measures and data governance policies to ensure the integrity and confidentiality of data.
- Optimize data workflows for performance, reliability, and cost-effectiveness on the GCP infrastructure.
