• Job Description

  Req#: 44631

  Basic Qualifications:

  • Bachelor’s or Master’s degree in a Computer Science, Engineering or a related or related field of study
  • 5+ Years - Ability to work effectively across organizations, product teams and business partners.
  • 5+ Years - Knowledge Agile (Scrum) Methodology, experience in writing user stories
  • 5+ Years - Strong understating of Database concepts and experience with multiple database technologies – optimizing query and data processing performance.
  • 5+ Years - Full Stack Data Engineering Competency in a public cloud – Google, MS Azure, AWS
  • Critical thinking skills to propose data solutions, test, and make them a reality.
  • 5+ Years - Highly Proficient in SQL, Python, Java, Scala, or Go (or similar) - Experience programming engineering transformation in Python or a similar language.
  • 5+ Years Demonstrated ability to lead data engineering projects, design sessions and deliverables to successful completion.
  • Cloud native technologist
  • Deep understanding of data service ecosystems including data warehousing, lakes, metadata, meshes, fabrics and AI/ML use cases.
  • User experience advocacy through empathetic stakeholder relationship.
  • Effective Communication both internally (with team members) and externally (with stakeholders)
  • Knowledge of Data Warehouse concepts – experience with Data Warehouse/ ETL processes
  • Strong process discipline and thorough understating of IT processes (ISP, Data Security).

  Qualifications

  Preferred Qualifications:

  • Excellent communication, collaboration and influence skills; ability to energize a team.
  • Knowledge of data, software and architecture operations, data engineering and data management standards, governance and quality
  • Hands on experience in Python using libraries like NumPy, Pandas, etc.
  • Extensive knowledge and understanding of GCP offerings, bundled services, especially those associated with data operations Cloud Console, BigQuery, DataFlow, DataFusion, PubSub / Kafka, Looker Studio, VertexAI
  • Experience with Teradata, Hadoop, Hive, Spark and other parts of legacy data platform
  • Experience with recoding, re-developing and optimizing data operations, data science and analytical workflows and products.
  • Data Governance concepts including GDPR (General Data Protection Regulation), CCPA (California Consumer Protection Act), PoLP and how these can impact technical architecture

  Responsibilities

  Responsibilities:

  • Interact with GDIA product lines and business partners to understand data engineering opportunities, tooling and needs.
  • Collaborate with Data Engineering and Data Architecture to design and build templates, pipelines and data products including automation, transformation and curation using best practices
  • Develop custom cloud solutions and pipelines with GCP native tools – Data Prep, Data Fusion, Data Flow, DBT and Big Query
  • Operationalize and automate data best practices: quality, auditable, timeliness and complete
  • Participate in design reviews to accelerate the business and ensure scalability
  • Work with Data Engineering and Architecture and Data Platform Engineering to implement strategic solutions
  • Advise and direct team members and business partners on Ford standards and processes.

• About the company

  Ford is a global company with shared ideals and a deep sense of family. From our earliest days as a pioneer of modern transportation.

Notice