Data Architect

Role & Responsibilities

• Utilize Google Cloud Platform & Data Services to modernize legacy applications.
• Understand technical business requirements and define architecture solutions that align to Ford Motor & Credit Companies Patterns and Standards.
• Collaborate and work with global architecture teams to define analytics cloud platform strategy and build Cloud analytics solutions within enterprise data factory.
• Provide Architecture leadership in design & delivery of new Unified data platform on GCP.
• Understand complex data structures in analytics space as well as interfacing application systems. Develop and maintain conceptual, logical & physical data models. Design and guide Product teams on Subject Areas and Data Marts to deliver integrated data solutions.
• Leverage cloud AI/ML Platforms to deliver business and technical requirements.
• Provide architectural guidance for optimal solutions considering regional Regulatory needs.
• Provide architecture assessments on technical solutions and make recommendations that meet business needs and align with architectural governance and standard.
• Guide teams through the enterprise architecture processes and advise teams on cloud-based design, development, and data mesh architecture.
• Provide advisory and technical consulting across all initiatives including PoCs, product evaluations and recommendations, security, architecture assessments, integration considerations, etc.
  

Responsibilities

Required Skills and Selection Criteria:

• Google Professional Solution Architect certification.
• 8+ years of relevant work experience in analytics application and data architecture, with deep understanding of cloud hosting concepts and implementations.
• 5+ years’ experience in Data and Solution Architecture in analytics space. Solid knowledge of cloud data architecture, data modelling principles, and expertise in Data Modeling tools.
• Experience in migrating legacy analytics applications to Cloud platform and business adoption of these platforms to build insights and dashboards through deep knowledge of traditional and cloud Data Lake, Warehouse and Mart concepts.
• Good understanding of domain driven design and data mesh principles.
• Experience with designing, building, and deploying ML models to solve business challenges using Python/BQML/Vertex AI on GCP.
• Knowledge of enterprise frameworks and technologies. Strong in architecture design patterns, experience with secure interoperability standards and methods, architecture tolls and process.
• Deep understanding of traditional and cloud data warehouse environment, with hands on programming experience building data pipelines on cloud in a highly distributed and fault-tolerant manner. Experience using Dataflow, pub/sub, Kafka, Cloud run, cloud functions, Bigquery, Dataform, Dataplex , etc.
• Strong understanding on DevOps principles and practices, including continuous integration and deployment (CI/CD), automated testing & deployment pipelines.
• Good understanding of cloud security best practices and be familiar with different security tools and techniques like Identity and Access Management (IAM), Encryption, Network Security, etc. Strong understanding of microservices architecture.
  

Qualifications

Nice to Have

• Bachelor’s degree in Computer science/engineering, Data science or related field.
• Strong leadership, communication, interpersonal, organizing, and problem-solving skills
• Good presentation skills with ability to communicate architectural proposals to diverse audiences (user groups, stakeholders, and senior management).
• Experience in Banking and Financial Regulatory Reporting space.
• Ability to work on multiple projects in a fast paced & dynamic environment.
• Exposure to multiple, diverse technologies, platforms, and processing environments.