Global Data Insight & Analytics (GDI&A) aspire to navigate Ford Motor Company through the disruptiveness of the information age, harnessing the power of data and artificial intelligence to realize the enterprise’s known goals, reveal hidden opportunities, and achieve data superiority.
Within GDI&A, we are building a new global team responsible for the strategy & delivery of 360 data services, modern business intelligence, and advanced analytics solutions powering Ford. This enables Ford to operate as an analytics-driven business in a competitive marketplace.
We are seeking experienced GCP Data & Analytics professionals to add to our product teams to drive the next generation of products. GDI&A Cloud Data Engineers work in a Product Management Delivery model working end-to-end with business partners, analytics managers, product owners, product designers, data scientists, business intelligence engineers, and software developers to deliver analytics innovation.
Develop EL/ELT/ETL pipelines to make data available in BigQuery analytical data store from disparate batch, streaming data sources for the Supply Chain
Work with on-prem data sources (Hadoop, SQL Server) and Cloud data sources (GCP) to understand the data model, and business rules behind the data and build data pipelines (with GCP) for one or more business domains.
Build cloud-native services and APIs to support and expose data-driven solutions.
Partner closely with our data scientists to ensure the right data is made available promptly to deliver compelling and insightful solutions.
Design, build, and launch shared data services to be leveraged by the internal and external partner developer community.
Building out scalable data pipelines and choosing the right tools for the right job. Manage, optimize, and Monitor data pipelines.
Provide extensive technical, and strategic advice and guidance to key stakeholders around data transformation efforts. Understand how data is useful to the enterprise.
Bachelor’s Degree in Data Science, Data Analytics, Computer Science, Computer Engineering, Applied Math, Statistics, or related quantitative field
7+ years of Programming experience utilizing Python and SQL
5+ years in a traditional data warehouse environment (ETL pipelines)
3+ years of experience building out data pipelines from scratch in a highly distributed and fault-tolerant manner.
2+ years of experience working on cloud-based systems (ideally Google Cloud) or AWS where you utilized the understanding of the simplicity and scalability of data pipelines and interfaces.
Experience with any of the following: BigQuery, Airflow, Dataflow, Cloud Run, DBT, and/or PubSub
A strong technical background, with experience building applications in a data-focused role in both Cloud and Traditional Data Warehouses
Requisition ID : 24970
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