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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Ford Motor Company - **Location:** Honolulu, HI, United States (Remote available) - **Experience:** Experienced - **Salary:** $115,000.0 - $192,900.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Java (Programming Language), Application Programming Interfaces (APIs), Airflow, BigQuery, Cloud Storage, Cluster Analysis, Code Review, Information Systems, Computer Programming, Continuous Integration, Data Architecture, Data Validation, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Systems, Data Visualization, Database Queries, Dimensional Modeling, Document-Oriented Databases, Data Flow Control, Python (Programming Language), Meta-Data Management, Software Maintenance, Query Optimization, Raw Data, Power BI, Cloud Services, Software Deployment, Software Engineering, SQL Databases, Data Streaming, Systems Architecture, Tableau (Software), Workflow Management Systems, Openapi, Google Cloud, Flask (Web Framework), Data Build Tool (dbt), Backend, Git, Fastapi, Data Layers, Kotlin, Containerization, Kubernetes, Information Technology, Data Lineage, Collibra, Google Cloud Functions, Star Schema, Google Bigquery, Apache Kafka, Graphql, Api Design, Restful APIs, Terraform, Domain Driven Design, Looker Analytics, Software Version Control, Data Pipelines, Api Management, Docker - **Published:** September 27, 2026 - **Apply:** https://dejobs.org/x/x/64806504E23D4887A05AC3F5D1AC1F86/job/ ## About the Role * Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field or equivalent combination of relevant education and experience. * 5+ years of experience in data engineering, software engineering, or a full-stack data role. * 3+ years in roles demonstrating Strong programming skills in Python, Kotlin, and Java * 3 years of Strong hands-on experience with Google BigQuery (data modeling, query optimization, cost management, scheduled queries). * 3+ years of Proven experience designing and building APIs (REST and/or GraphQL) using frameworks such as FastAPI, Flask, Node.js/Express, or similar. * 3 years of practical experience building and maintaining a semantic layer (e.g., dbt, LookML/Looker, Cube.js, AtScale) to standardize business metrics. * 2+ years of experience in roles requiring a Strong understanding of testing, monitoring, reliability, and maintainable software design * 2+ years comfortable working years of experience with SQL and structured data Even better, you may have... * Master's degree in Computer Science, Engineering, Information Systems, or a related field * Document data flows, API specifications, semantic definitions, and system architecture for internal and cross-team use. * Experience working with a data catalog / metadata management tool (e.g., Google Data Catalog, Collibra, Alation, Atlan, Amundsen) including lineage, tagging, and governance workflows. * Strong SQL skills and experience with Python for data pipeline development and automation. * Experience with cloud platforms, preferably Google Cloud Platform (GCP) (Cloud Storage, Cloud Functions, Dataflow, Pub/Sub, Composer/Airflow). * Solid understanding of data modeling concepts (dimensional modeling, star/snowflake schemas, normalization). * Familiarity with version control (Git) and CI/CD practices for data and application deployments. * Strong understanding of data governance, security, and privacy best practices. * Experience with orchestration tools such as Apache Airflow / Cloud Composer. * Familiarity with dbt (data build tool) for transformation and testing. * Experience with containerization (Docker/Kubernetes) and infrastructure-as-code (Terraform). * Exposure to streaming data platforms (Kafka, Pub/Sub, Dataflow). * Experience in the automotive, manufacturing, or connected vehicle data domain (a plus, given Ford's business context). * Knowledge of BI/visualization tools (Looker, Tableau, Power BI). * Understanding of data mesh or domain-driven data architecture principles. ## Description We are looking for a Full Stack Data Engineer to design, build, and maintain end-to-end data solutions - from raw data ingestion and API development through to curated semantic layers that power analytics and business decision-making. * Design, build, and maintain scalable ETL/ELT pipelines to ingest, transform, and deliver data from diverse sources into Google BigQuery and other cloud data platforms. * Develop, document, and maintain RESTful/GraphQL APIs to expose data and services to internal applications, dashboards, and third-party consumers. * Design and manage a semantic data layer (e.g., LookML, dbt semantic models, Cube.js, or similar) that translates raw data into consistent, business-friendly metrics and definitions. * Implement and maintain a data catalog / knowledge catalog (e.g., Google Data Catalog, Collibra, Alation, Atlan) to improve data discoverability, lineage tracking, and metadata management. * Optimize BigQuery performance through partitioning, clustering, query tuning, and cost-management best practices. * Build data quality checks, monitoring, and alerting to ensure pipeline reliability and data trustworthiness.Collaborate with cross-functional teams (analytics, product, engineering) to gather requirements and translate them into scalable data models and API contracts. * Enforce data governance, security, and access control standards (PII handling, role-based access, encryption). * Write clean, well-tested, and maintainable code (Python/SQL, and backend frameworks for APIs). * Participate in code reviews, architecture discussions, and CI/CD pipeline development for data and application deployments. ## Related Videos - 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