Ford Motor Company संयुक्त राज्य अमेरिका की एक ऑटोमोबाइल निर्माता कंपनी है, जिसका इतिहास 1903 से जुड़ा है। वाहनों के विकास और उत्पादन के अलावा, कंपनी मोबिलिटी सेवाओं, डिजिटल अनुभवों और सॉफ़्टवेयर पर भी अपना ध्यान बढ़ा रही है। Ford के कार्यों में स्थिरता से जुड़े प्रयास और पर्यावरणीय लक्ष्य भी शामिल हैं, जो परिवहन, नवाचार, सामुदायिक प्रभाव और जिम्मेदार व्यावसायिक प्रक्रियाओं को जोड़ने वाले दृष्टिकोण को दर्शाते हैं।
Full-Stack Data Engineer at Ford
Build scalable GCP data pipelines and platforms for Ford’s enterprise technology organization. Support governance, security, automation, and performance improvements.
विवरण
- Create and maintain scalable ingestion and curation pipelines from varied data sources.
- Standardize and improve data quality so it is ready for analytics.
- Develop efficient data pipelines with Python, SQL, and DBT or Dataform.
- Support end-to-end development and dependable data movement from source to insight.
- Build and operate GCP data platforms using BigQuery, Dataflow, Pub/Sub, and Cloud Functions.
- Apply data governance policies, access controls, and cloud security practices.
- Manage data workflows and provision cloud infrastructure with Astronomer and Terraform.
- Improve pipeline and storage performance, scalability, efficiency, resource use, and cost effectiveness.
- Work with data and application architects, service owners, and cross-functional teams to establish practices, design patterns, and frameworks.
- Automate platform operations to strengthen reliability, data quality, and efficiency.
- Explain complex technical decisions to technical and non-technical stakeholders.
- Find ways to improve the data platform and extend its capabilities.
- Turn business needs into effective data asset designs and efficient code.
- Document data engineering processes and encourage knowledge sharing.
आवश्यकताएँ
- Bachelor’s degree in computer science, information technology, information systems, data analytics, or a related area, or an equivalent combination of education and experience.
- Five to seven years in data engineering or software engineering, including at least two years building and deploying cloud data platforms; GCP experience is preferred.
- Strong command of SQL, Java, and Python.
- Hands-on experience designing and deploying cloud data pipelines with GCP services such as BigQuery, Dataflow, and DataProc.
- Understanding of service-oriented architecture and microservices.
- Experience with relational databases such as PostgreSQL and MySQL, NoSQL databases, and columnar databases such as BigQuery.
- Knowledge of cloud data governance frameworks, encryption, and data masking.
- Familiarity with CI/CD pipelines, infrastructure as code tools such as Terraform and Tekton, and automation frameworks.
- Strong analytical and problem-solving abilities, including troubleshooting complex data platform and microservices issues.
- Experience monitoring and optimizing costs and compute resources for GCP services such as BigQuery, Dataflow, Cloud Run, and DataProc.
- Interest in data, innovation, and ongoing learning.