Data Engineer – Full Stack

🕒 Maio 8

🏈 Ohio – Remoto

🏈 Ohio – Remote

💵 $99.600 - $198.500 / ano

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🚰 Engenheiro de Dados

🦅 Patrocina Visto H1B

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Ford Motor Company

SiteLinkedInTodas as Vagas

10.000+ funcionários

Fundada em 1903

🚗 Transporte

💰 Post-IPO Debt em 2023-08

Transport • Manufacturing • Sustainability

A Ford Motor Company é uma empresa automotiva de renome global sediada nos Estados Unidos, fundada por Henry Ford. A empresa está comprometida em construir um mundo melhor, onde cada indivíduo tenha a liberdade de se mover e seguir seus sonhos. A Ford é dedicada à inovação, com foco em serviços, experiências e software, além de sua tradicional fabricação de veículos. A empresa está ativamente envolvida em iniciativas de sustentabilidade e pretende cumprir metas ambientais ambiciosas. A Ford valoriza o serviço, o impacto na comunidade e se esforça para combinar sucesso nos negócios com responsabilidade social e ambiental. Com uma rica história de mais de 121 anos, a Ford continua a se adaptar e liderar no cenário automotivo em evolução.

Descrição

• Design and implement end-to-end data pipelines (ETL/ELT) that ingest, process, and curate large-scale enterprise data, including telemetry/vehicle data and other structured/unstructured sources. • Build and maintain Gen AI pipelines — including embedding generation, vector store indexing, retrieval-augmented generation (RAG), and LLM orchestration — to enable intelligent search, summarization, and conversational analytics over enterprise data. • Migrate and modernize data assets to a centralized data platform (e.g., BigQuery) using principled data lake/warehouse architectures (Bronze/Silver/Gold or Medallion architecture) to power analytics, reporting, and AI/ML workloads. • Architect scalable data models and data warehouses, optimizing for query performance, maintainability, cost efficiency, and downstream AI consumption. • Develop and operate robust orchestration pipelines using Airflow/Astronomer or Schedule Query, with secure, reproducible CI/CD workflows (Terraform + Git) for both data and AI artifacts. • Integrate LLM APIs and AI services (e.g., Vertex AI, OpenAI, LangChain) into data workflows to automate data enrichment, classification, anomaly narratives, and natural-language interfaces. • Build and maintain reliable data and model quality checks, lineage, and monitoring with observability tools (e.g., Splunk, Looker/Grafana/Tableau/Power BI dashboards) to rapidly detect and resolve data and AI pipeline issues. • Implement data governance, security, and compliance controls (data lineage, access controls, PII/PHI protection, prompt injection safeguards, responsible AI guardrails) in collaboration with security and privacy teams. • Lead the design and delivery of analytics-ready and AI-ready data assets for cross-functional teams, including dashboards, alerts, self-service analytics, and AI-powered insight tools. • Evaluate, prototype, and productionize emerging Gen AI capabilities (agents, function calling, fine-tuning, multimodal models) to solve business problems and improve platform intelligence. • Mentor and coach junior engineers on data engineering, AI/ML integration patterns, prompt engineering best practices, and documentation standards. • Collaborate with data scientists, ML engineers, product managers, and business stakeholders to translate requirements into scalable data and AI solutions and timely insights. • Monitor cost and capacity planning for cloud and AI resources; optimize storage, compute, and token usage across GCP services (BigQuery, Dataflow, Dataproc, GCS, Vertex AI). • Participate in on-call rotations and incident response to maintain high availability of data and AI services.

🎯 Requisitos

• A bachelor's degree • 5+ years of experience in data engineering, data platforms, or a similar role. • 3+ years of hands-on experience with Google Cloud Platform (BigQuery, Cloud Storage, Dataflow, Dataproc; Schedule Query or equivalent scheduling/orchestration) or AWS. • 1+ years of experience working with Generative AI technologies — including LLMs, embeddings, vector databases, RAG architectures, or AI orchestration frameworks (e.g., LangChain, Semantic Kernel, LlamaIndex). • 1+ year experience building Semantic Data layer to serve AI agents. • Practical experience building and operating data pipelines with orchestration tools (Airflow/Astronomer; Schedule Query). • Experience with infrastructure-as-code and CI/CD (Terraform, Git, and related tooling). • Demonstrated ability to design and implement analytics-ready data assets and dashboards; familiarity with BI tools (Looker, Tableau, Power BI, Grafana) for monitoring and reporting. • Strong communication skills and ability to work effectively with cross-functional teams (engineering, analytics, product, security).

🏖️ Benefícios

• Immediate medical, dental, vision and prescription drug coverage • Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more • Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more • Vehicle discount program for employees and family members and management leases • Tuition assistance • Established and active employee resource groups • Paid time off for individual and team community service • A generous schedule of paid holidays, including the week between Christmas and New Year’s Day • Paid time off and the option to purchase additional vacation time