Data Scientist

Role Overview

In Global Data Insight & Analytics (GDI&A), we harness the power of data and artificial intelligence to navigate Ford Motor Company through the disruptiveness of the information age. We are looking for a hands-on Data Engineer with 3+ years of experience building production-grade data pipelines, cloud data platforms, and automated data workflows to support modern AI, ML, and GenAI use cases.

Responsibilities

• Design, build, and maintain reliable batch and streaming data pipelines for ingestion, transformation, validation, and publishing.
• Develop curated, reusable, and well-documented data products that support BI dashboards, analytics applications, ML models, and GenAI-enabled solutions.
• Implement strong data quality checks, observability, lineage, metadata management, and monitoring practices.
• Write clean, modular, and well-tested code using Python and SQL.
• Use cloud-native technologies such as BigQuery, Dataflow, Dataproc, Cloud Composer/Airflow, Dataform, DBT, or Spark.
• Enable AI/ML and GenAI teams by preparing high-quality feature datasets and vector-ready datasets.
• Apply DataOps practices including CI/CD, version control, and automated testing.
• Optimize pipeline performance, storage usage, and compute cost.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field.
• 3+ years of hands-on experience in data engineering, ETL/ELT development, or cloud-based data platform delivery.
• Strong proficiency in SQL and Python.
• Experience designing and operating scalable pipelines on cloud platforms such as Google Cloud Platform, AWS, or Azure.
• Experience with modern data platforms like BigQuery, Spark, Airflow, or DBT.
• Good understanding of data modeling, partitioning, and performance tuning.
• Familiarity with Git and CI/CD.

Skills

• Python
• SQL
• Google Cloud Platform
• Apache Spark
• Apache Airflow