Full Stack Software Engineer - Teradata/ETL/DataStage

Full Stack Software Engineer - Teradata/ETL/DataStage - positions offered by Ford Motor Company (Dearborn, Michigan). Note, this is a hybrid position whereby the employee will work both from home and from the aforementioned worksite. Hence, the employee must live within a reasonable commuting distance from the worksite. Lead the design, development, and deployment of robust, scalable, and high-performance data pipelines on GCP. Drive the migration of on-premise and legacy data processes to native GCP services. Implement and manage CI/CD pipelines using Tekton for automated data pipeline deployments and testing. Utilize Terraform to provision and manage GCP infrastructure as code, ensuring consistency and repeatability. Manage source code, collaborate on development, and enforce best practices using GitHub. Work extensively with GCP services such as Big Query, Dataflow, IBM CloudPak, and Apache Airflow. Collaborate with cross-functional teams to understand data requirements and translate them into technical solutions. Conduct thorough analysis of existing data systems, identify areas for improvement, and integrate diverse data sources. Perform rigorous performance tuning and optimization of data pipelines and queries. Provide proactive production support, diagnosing and resolving complex technical challenges efficiently. Actively participate in code reviews, mentor junior engineers, and contribute to the evolution of engineering best practices and coding standards. Contribute to data modeling efforts, potentially using tools like Power Designer.

Bachelor's degree or foreign equivalent in Computer Science or Information Technology and 7 years of progressive, post-baccalaureate experience in the job offered or a related occupation. 5 years of experience with each of the following skills is required: 1. Using Teradata ecosystem, including BTEQ, FastLoad, MultiLoad, and Tpump. 2. Designing and building ETL pipelines and data warehouses using PL/SQL. 3. Understanding of data warehousing concepts, including dimensional modelling (star/snowflake schemas) and data integrity. 4. Using SQL with performance tuning complex queries. 5. UNIX/Linux environments and shell scripting. 6. Data modelling and designing logical and physical database schemas. 3 years of experience with each of the following skills is required: 1. Developing complex ETL workflows with IBM DataStage. 2. Systems analysis, production support, and root cause analysis for data-related issues. 3. Creating and executing test plans for data quality and reconciliation. 1 year of experience with each of the following skills is required: 1. Understanding of data governance principles, including coding standards, code review processes, and metadata management. 2. Working with sensitive data (PPI) and understanding the associated security and handling requirements., Bachelor's degree or foreign equivalent in Computer Science or Information Technology and 7 years of progressive, post-baccalaureate experience in the job offered or a related occupation. 5 years of experience with each of the following skills is required: 1. Using Teradata ecosystem, including BTEQ, FastLoad, MultiLoad, and Tpump. 2. Designing and building ETL pipelines and data warehouses using PL/SQL. 3. Understanding of data warehousing concepts, including dimensional modelling (star/snowflake schemas) and data integrity. 4. Using SQL with performance tuning complex queries. 5. UNIX/Linux environments and shell scripting. 6. Data modelling and designing logical and physical database schemas. 3 years of experience with each of the following skills is required: 1. Developing complex ETL workflows with IBM DataStage. 2. Systems analysis, production support, and root cause analysis for data-related issues. 3. Creating and executing test plans for data quality and reconciliation. 1 year of experience with each of the following skills is required: 1. Understanding of data governance principles, including coding standards, code review processes, and metadata management. 2. Working with sensitive data (PPI) and understanding the associated security and handling requirements.