Full Stack Data Engineer

Ford Motor Company

. Design, develop, and maintain scalable data ingestion and curation pipelines from diverse sources .

Posted 9/24/2026full-timeRemote • MexicoMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and managing scalable data platforms on Google Cloud Platform (GCP) using tools like BigQuery and Dataflow, while ensuring data governance and quality. Proficient in SQL and Python, with a strong focus on optimizing data ingestion and curation processes for analytical use.

Highest-signal resume keywords

Google Cloud Platform (GCP)BigQueryDataflowSQLPython

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringCloud-Based Data PlatformsData GovernanceData Quality Best PracticesAutomation FrameworksRelational DatabasesNoSQL DatabasesMicroservicesAPI-Based IntegrationsCloud Cost Optimization

Soft Skills

CommunicationCollaboration

Tools & Technologies

TerraformAstronomerCI/CD PipelinesDataprocApache Airflow

Industry Keywords

Data IngestionData CurationService-Oriented Architecture (SOA)Encryption TechniquesData Masking Techniques

Tech Stack

Tools & technologies

AirflowApacheBigQueryCloudGoogle Cloud PlatformMicroservicesMySQLNoSQLPostgresPythonSQLTerraform

About the role

Key responsibilities & impact

Design, develop, and maintain scalable data ingestion and curation pipelines from diverse sources
Standardize, improve the quality of, and optimize data for analytical use
Contribute to seamless end-to-end development and reliable data flow from source to insight
Build and manage GCP data platforms using BigQuery, Dataflow, Pub/Sub, Cloud Functions, and related services
Implement and manage data governance policies, access controls, and security best practices
Use Astronomer and Terraform for workflow management and cloud infrastructure provisioning
Monitor and improve pipeline and storage performance, scalability, efficiency, resource utilization, and cost-effectiveness
Collaborate with data architects, application architects, service owners, and cross-functional teams on best practices, design patterns, and frameworks
Automate data platform processes to improve reliability, data quality, and operational efficiency
Communicate technical decisions to technical and non-technical stakeholders
Translate business requirements into data asset designs and efficient code
Document data engineering processes and promote knowledge sharing

Requirements

What you’ll need

Bachelor's degree in Computer Science, Information Technology, Information Systems, Data Analytics, Engineering, or a related field, or equivalent practical experience
5 to 7 years of experience in Data Engineering or Software Engineering
Strong English skills
Minimum 2 years of hands-on experience building and deploying cloud-based data platforms, preferably on Google Cloud Platform (GCP)
Strong proficiency in SQL and Python
Experience with BigQuery, Dataflow, Dataproc, and cloud-based data processing technologies
Experience with Terraform, CI/CD pipelines, and automation frameworks
Knowledge of cloud security, data governance, and data quality best practices
Experience with relational databases such as PostgreSQL and MySQL, as well as NoSQL and columnar databases
Understanding of Service-Oriented Architecture (SOA) and microservices-based solutions
Knowledge of encryption and data masking techniques
Ability to monitor, troubleshoot, and optimize cloud workloads for performance, scalability, and cost efficiency
Preferred: experience with DBT, Dataform, Apache Airflow, Astronomer, microservices, API-based integrations, FinOps, and cloud cost optimization

Benefits

Comp & perks

Equal opportunity employer committed to a diverse and inclusive workplace
Remote work arrangement
Opportunities to collaborate with cross-functional teams
Continuous learning about industry trends and emerging technologies
Knowledge sharing and documentation practices