Sr. Data Engineering Manager

We are the movers of the world and the makers of the future. We get up every day, roll up our sleeves and build a better world -- together. At Ford, we’re all a part of something bigger than ourselves. What will you make today?

At Ford Motor Credit Company, we are modernizing enterprise Core Platforms and integrating new lending platform to Google Cloud Data Platform (Data Factory), to improve Data, Analytics and AI/ML capabilities, and enhance customer experience, regulatory compliance & operational efficiencies, enabled by Google Cloud.

This position will lead integration of core data from New North America Lending platforms into Data Factory (GCP BQ), and build upon the existing analytical data, including merging historical data from legacy platforms with data ingested from new platforms. To enable critical regulatory reporting, operational analytics, risk analytics and modeling

Will provide overall technical guidance to implementation teams and oversee adherence to engineering patterns and data quality and compliance standards, across all data factory workstreams. Support business adoption of data from new platform and sunset of legacy platforms & technology stack.

This position will collaborate with technical program manager, data platform enablement manager, analytical data domain leaders, subject matter experts, supplier partners, business partner and IT operations teams to deliver the Data integration workstream plan following agile framework.

We are looking for dynamic, technical leader with prior experience of leading data warehouse as part of complex business & tech transformation. Has strong experience in Data Engineering, GCP Big Query, Data ETL pipelines, Data architecture, Data Governance, Data protection, security & compliance, and user access enablement.

 Key responsibilities -  

1. This role will focus on implementing data integration of new lending platform into Google Cloud Data Platform (Data factory), existing analytical domains and building new data marts, while ensuring new data is integrated seamlessly with historical data. 
2. Will lead a dedicated team of data engineers & analysts to understand and assess new data model and attributes, in upstream systems, and build an approach to integrate this data into factory.
3. Will lead the data integration architecture (in collaboration with core mod platform & data factory architects) and designs, and solution approach for Data Factory
4. Will understand the scope of reporting for MMP (Minimal Marketable Product) launch & build the data marts required to enable agreed use cases for regulatory, analytical & operational reporting, and data required for Risk modeling. 
5. Will collaborate with Data Factory Analytical domain teams, to build new pipelines & expansion of analytical domains. 
6. Will lead data integration testing strategy & its execution within Data Factory (end-to-end, from ingestion, to analytical domains, to marts) to support use cases.
7. Will be Data Factory SPOC for all Core Modernization program and help facilitate & prioritize backlogs of data workstreams.
8. Ensure the data solutions are aligned to overall program goals, timing and are delivered with quality
9. Collaborate with program managers to plan iterations, backlogs and dependencies across all workstream to progress workstreams at required pace.
10. Drive adoption of standardized architecture, design and quality assurance approaches across all workstreams and ensure solutions adheres to established standards.
11. People leader for a team of 5+ data engineers and analysts. Additionally manage supplier partner team who will execute the migration plan
12. Lead communication of status, issues & risks to key stakeholders

You'll have…..

• Bachelor’s degree in computer science or equivalent
• 5+ years of experience delivering complex Data warehousing projects and leading teams of 10+ engineers and suppliers to build Big Data/Datawarehouse solutions.
• 10+ years of experience in technical delivery of Data Warehouse Cloud Solutions for large companies, and business adoption of these platforms to build analytics , insights & models
• Prior experience with cloud data architecture, data modelling principles, DevOps, security and controls 
• Google Cloud certified - Cloud Data Engineer preferred.
• Hands on experience of the following:
  • Orchestration of data pipelines (e.g. Airflow, DBT, Dataform, Astronomer).
  • Batch data pipelines (e.g. BQ SQL, Dataflow, DTS).
  • Streaming data pipelines (e.g. Kafka, Pub/Sub, gsutil)
  • Data warehousing techniques (e.g. data modelling, ETL/ELT).

 

Even better, you may have….

• Master’s degree