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Ford Motor Company · 9 hours ago

Data Engineer

Dearborn, MI

Full-time

Hybrid

Mid, Senior Level

4+ years exp

Ford Motor Company believes in freedom of movement and is looking for a Data Engineer to join their Electric Vehicle organization. The role involves building scalable data pipelines and working with connected vehicle data to support prognostic initiatives.

AutomotiveAutonomous VehiclesManufacturingTransportation

No H1B

Responsibilities

Develop exceptional analytical data products using both streaming and batch ingestion patterns on Google Cloud Platform with solid data warehouse principles

Build data pipelines to monitoring quality of data and performance of analytical models

Maintain the infrastructure of the data platform using terraform and continuously develop, evaluate, and deliver code using CI/CD

Collaborate with data analytics stakeholders to streamline the data acquisition, processing, and presentation process

Implement an enterprise data governance model and actively promote the concept of data - protection, sharing, reuse, quality, and standards

Enhance and maintain the DevOps capabilities of the data platform

Continuously optimize and enhance existing data solutions (pipelines, products, infrastructure) for best performance, high security, low vulnerability, low costs, and high reliability

Work in an agile product team to deliver code frequently using Test Driven Development (TDD), continuous integration and continuous deployment (CI/CD)

Promptly address code quality issues using SonarQube, Checkmarx, Fossa, and Cycode throughout the development lifecycle

Perform any necessary data mapping, data lineage activities and document information flows

Monitor the production pipelines and provide production support by addressing production issues as per SLAs

Provide analysis of connected vehicle data to support new product developments and production vehicle improvements

Provide visibility to data quality/vehicle/feature issues and work with the business owners to fix the issues

Demonstrate technical knowledge and communication skills with the ability to advocate for well-designed solutions

Continuously enhance your domain knowledge of connected vehicle data, connected services and algorithms/models developed by data scientists within Ford

Stay current on the latest data engineering practices and contribute to the technical direction of the company while keeping a customer-centric approach

Qualification

Data engineeringCloud data engineeringData pipeline developmentMachine LearningGoogle Cloud PlatformJavaPythonSQLApache KafkaTerraformSoft skills

Required

Master's degree or foreign equivalent degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related field, and 4 years of experience OR equivalent combination of education and experience (6+ years with Bachelor's Degree)

4 years of professional experience in: Data engineering, data product development and software product launches

At least three of the following languages: Java, Python, Spark, Scala, SQL

3 years of cloud data/software engineering experience building scalable, reliable, and cost-effective production batch and streaming data pipelines using: Data warehouses like Amazon Redshift, Microsoft Azure Synapse Analytics, Google BigQuery

Workflow orchestration tools like Airflow

Relational Database Management System like MySQL, PostgreSQL, and SQL Server

Real-Time data streaming platform like Apache Kafka, GCP Pub/Sub

Microservices architecture to deliver large-scale real-time data processing application

REST APIs for compute, storage, operations, and security

DevOps tools such as Tekton, GitHub Actions, Git, GitHub, Terraform, Docker

Project management tools like Atlassian JIRA

Preferred

Ph.D. or foreign equivalent degree in Computer Science, Software Engineering, Information System, Data Engineering, or a related field

2 years of experience with ML Model Development and/or MLOps

Committed code to improve open-source data/software engineering projects

Experience architecting cloud infrastructure and handling application migrations/upgrades

GCP Professional Certifications

Demonstrated passion to mine raw data and realize its hidden value

Passion to experiment/implement state of the art data engineering methods/techniques

Experience working in an implementation team from concept to operations, providing deep technical subject matter expertise for successful deployment

Experience implementing methods for automation of all parts of the pipeline to minimize labor in development and production

Analytics skills to profile data, troubleshoot data pipeline/product issues

Ability to simplify, clearly communicate complex data/software ideas/problems and work with cross-functional teams and all levels of management independently