Data Engineer

Ford Motor Company

. Design, build, test and operate ingestion and processing pipelines from plant OT sources into GCP .

Posted 9/29/2026full-timeNaucalpan de Juárez • MexicoMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and operating data ingestion and processing pipelines using GCP tools, with a strong focus on data quality, modeling, and governance. Proven ability to mentor engineers and lead complex technical projects while ensuring efficient data management and compliance.

Highest-signal resume keywords

Data Engineering ExperienceAdvanced SQLStrong PythonGCP ProficiencyData Modeling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IngestionData ProcessingData Quality ControlData ModelingBatch ProcessingStreaming Data ProcessingVersion ControlAutomated TestingCI/CDInfrastructure as Code

Soft Skills

Team PlayerProblem SolverAgile MethodologyMentoringCommunication

Tools & Technologies

GCPBigQueryPub/SubDataflowCloud SQLCloud StorageCloud ComposerGitHub Actions

Industry Keywords

OT SourcesData GovernanceCybersecurityData PrivacyIncident Response

Tech Stack

Tools & technologies

BigQueryCloudCyber SecurityGoogle Cloud PlatformPostgresPythonSQL

About the role

Key responsibilities & impact

Design, build, test and operate ingestion and processing pipelines from plant OT sources into GCP
Work with PLC event data, sensor streams, waveform captures, energy meters and image capture
Build batch and streaming pipelines using Pub/Sub, Dataflow, Cloud Run/Functions, Cloud Composer, BigQuery and Cloud SQL/PostgreSQL
Handle high-volume unstructured image and video data, including object storage, lifecycle and cost management, frame sampling and metadata indexing
Own production pipelines including monitoring, alerting, cost, backfill, recovery and incident response
Design and maintain data models, semantic layers, common data models and plant, line, station, asset and tool hierarchies
Implement data quality controls for validation, completeness, drift, latency and lineage
Optimize BigQuery storage, partitioning, query performance and cost
Prepare training and inference datasets for parametric and image-based anomaly detection models
Partner with data scientists on MLOps, reproducible datasets, versioning, monitoring and retraining triggers
Support edge inference requirements and build datasets for value evidence and dashboards
Apply data governance, privacy, retention and cybersecurity requirements across OT and IT boundaries
Manage access and identity for plant, product and enterprise consumers
Define reusable ingestion and onboarding patterns so adding a plant is configuration rather than a project
Set data engineering standards and lead technical design for significant data platform changes
Mentor and coach engineers and reduce single-person dependency on critical datasets and pipelines

Requirements

What you’ll need

Bachelor's degree in Computer Science, Data Engineering, Software Engineering or a related technical field, or equivalent demonstrable experience
Typically 5+ years of hands-on data engineering experience with production pipelines and data platforms designed, built and operated at scale
Advanced SQL and strong Python
Practical experience with GCP, including BigQuery, Pub/Sub, Dataflow, Cloud SQL, Cloud Storage and Composer
Experience with batch and streaming data processing and orchestration tooling
Experience with data modelling for analytical and operational use, data quality and validation
Software engineering fundamentals including version control, automated testing, CI/CD with GitHub Actions and infrastructure as code
Ability to work with imperfect industrial data and trace problems to source
Demonstrable experience mentoring and growing other engineers
Ability to lead complex technical work end to end and communicate data trade-offs clearly
Fluent professional English
Team player, problem solver and agile way of working
Availability to travel internationally on occasion to understand plant data at source

Benefits

Comp & perks

Equal opportunity and inclusive workplace commitment
International travel opportunities to Europe and the US
Mentorship and professional growth through technical coaching, pairing, design and code review
Opportunity to work with cutting-edge manufacturing, AI/ML, cloud and industrial technologies
Collaboration with global manufacturing teams and plant environments