Data Engineer - Manager

The Ford Customer Service Division Technology (FCSD Tech) group is seeking a data engineer people leader. The ideal candidate will lead and mentor a team of data engineers, designing and implementing scalable, reliable data pipelines in a GCP environment. The ideal candidate will have 10+ years experience, including 8+ years with SQL, Python, Teradata, and GCP cloud services (BigQuery, Dataflow, etc. ). Proven leadership and expertise in ETL processes, data architecture, and ensuring data quality and security are essential. Experience with big data tools (Spark, Hadoop) a plus.

• Bachelors degree in computer science, engineering or equivalent.
• 10+ years of work experience, including 8+ years with SQL, Python, Teradata, and cloud platforms (preferably GCP).
• Proven experience in leading a team and building data pipelines from scratch in a highly distributed and fault-tolerant manner.
• Familiarity with a broad array of relational and non-relational databases.
• Experience with GCP cloud services, including BigQuery, Cloud Composer, Dataflow, CloudSQL, GCS, Cloud Functions, and Pub/Sub.
• Strong communication skills and the ability to work in a dynamic environment.
• Inquisitive, proactive, and interested in learning new tools and techniques.
• Familiarity with big data and machine learning tools and platforms, including Apache Spark, Hadoop, and Kafka.
• Ability to guide and mentor the team.

• Lead a team of data engineers in gathering, transforming, and storing data through data acquisition, metadata management, data cleansing, data transformation, data distribution, and data recovery/backup planning.
• Hire, train, and equip the team with the necessary tools, skills, and resources to meet the organizations data needs.
• Design and implement data architecture using specialized ETL tools such as Informatica and Hyperion, considering long-term strategy and cost-effectiveness.
• Develop and maintain scalable ETL data pipelines in a cloud environment, moving data from various sources to the organizations data warehouse or data lake.
• Ensure data quality and accuracy by implementing data validation and testing processes, adopting a data quality framework, and performing code reviews.
• Manage data security to protect against unauthorized access or misuse, ensuring compliance with relevant regulations such as GDPR and HIPAA.
• Collaborate with data scientists, business intelligence developers, and software developers to ensure data availability and accessibility for business decisions.
• Stay up-to-date with the latest technologies and trends in data engineering, and lead the implementation of innovative solutions and practices.
• Manage project timelines and mitigate risks to ensure timely delivery of high-quality data engineering projects.