Enterprise Architect for Data and Analytics
3 days ago
We are seeking a highly skilled Enterprise Architect for Data and Analytics to join our team at Lennar Homes. As a key member of our organization, you will be responsible for designing, creating, and managing our data architecture, ensuring that our data is organized, accessible, secure, and aligned with business objectives.
Key Responsibilities- Interpret and deliver impactful strategic plans improving data integration, data quality, and data delivery in support of business initiatives and roadmaps.
- Design the structure and layout of data systems, including databases, warehouses, and lakes.
- Select and implement database management systems that meet the organization's needs by defining data schemas, optimizing data storage, and establishing data access controls and security measures.
- Define and implement the long-term technology strategy and innovations roadmaps across analytics, data engineering, and data platforms.
- Design and implement processes for the ETL process from various sources into the organization's data systems.
- Translate high-level business requirements into data models and appropriate metadata, test data, and data quality standards.
- Manage senior business stakeholders to secure strong engagement and ensures that the delivery of the project aligns with longer-term strategic roadmaps.
- Simplify the existing data architecture, delivering reusable services and cost-saving opportunities in line with the policies and standards of the company.
- Lead and participate in the peer review and quality assurance of project architectural artifacts across the EA group through governance forums.
- Define and manage standards, guidelines, and processes to ensure data quality.
- Work with IT teams, business analysts, and data analytics teams to understand data consumers' needs and develop solutions.
- Evaluate and recommend emerging technologies for data management, storage, and analytics.
- Support the development of business and information architecture governance structures and compliance activities.
- Optimize costs, output, and development effort by driving standardization, harmonization and reusability.
- Commercialize new technologies and platforms and supports pilot implementations.
- Enable a design assurance framework that ensures that projects and support activities are accomplished per Architecture guidelines.
- Act as mentor and coach on best practices across Digital, Data and Analytics technologies.
- Partner with strategic vendors to align product roadmaps and Lennar's architectural needs.
- Help key stakeholders shape information demand and aligns on effective use information assets.
- Education: BS/BA in Computer Science or related field or equivalent experience, data science, engineering, or related field.
- Experience: 10-15 years of relevant experience and at least 3-5 years' recent experience as an Information or Data Architect.
- Experience building large scale data processing and analytical systems.
- Experience leading projects involving data warehousing, data modeling, and data analysis.
- Design experience in Azure Databricks, PySpark, and Power BI/Tableau.
- Skills: Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP), real-time data distribution (Kafka, Dataflow), and modern data warehouse tools (Snowflake, Databricks).
- Experience with database technologies such as SQL, NoSQL, Oracle, Hadoop, or Teradata.
- Understanding of entity-relationship modeling, metadata systems, and data quality tools and techniques.
- Ability to think strategically and relate architectural decisions and recommendations to business needs and client culture.
- Ability to assess traditional and modern data architecture components based on business needs.
- Experience with business intelligence tools and technologies such as ETL, Power BI, and Tableau.
- Ability to regularly learn and adopt new technology, especially in the ML/AI realm.
- Strong analytical and problem-solving skills.
- Ability to synthesize and clearly communicate large volumes of complex information to senior management of various technical understandings.
- Understanding in programming languages such as Java, Python, and C/C++.
- Understanding in data science languages/tools such as SQL, R, SAS, or Excel.
- Ability to collaborate and excel in complex, cross-functional teams involving data scientists, business analysts, and stakeholders.
- Ability to guide solution design and architecture to meet business needs.
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