As a Vice President - Core Engineering (Data Architect) at Goldman Sachs, you will play a crucial role in defining, designing, and overseeing the implementation of enterprise-level data strategies, architectures, and solutions. Your responsibilities will include leading the development and execution of the organization's data strategy, architecting highly scalable data pipelines, ensuring data governance and quality, and providing technical leadership to cross-functional teams.

• *Key Responsibilities:**
- **Strategic Data Architecture & Roadmapping:**
- Lead the development of the organization's data strategy and architectural roadmap.
- Define data governance frameworks, data modeling, and real-time data platforms.
- **Complex Data System Design & Implementation:**
- Architect highly scalable data pipelines for large-scale data processing.
- Select appropriate technologies and patterns for data ingestion and storage.
- **Data Governance & Quality Leadership:**
- Implement data governance policies to ensure data quality and compliance.
- Design and maintain data catalogs and metadata management.
- **Advanced Data Modeling & Database Design:**
- Design and optimize data models for various data stores.
- Ensure performance, scalability, and flexibility in database design.
- **Technology Evaluation & Adoption:**
- Evaluate emerging data technologies and recommend their adoption.
- Drive innovation and efficiency within the data landscape.
- **Performance Optimization & Scalability:**
- Identify and resolve data-related performance bottlenecks.
- Ensure optimal performance and scalability of data platforms.
- **Technical Leadership & Mentorship:**
- Provide expert guidance and mentorship to data engineering teams.
- Foster best practices in data architecture and operational excellence.
- **Cross-Functional Collaboration & Stakeholder Management:**
- Collaborate with business stakeholders to translate requirements into data solutions.
- Ensure alignment with organizational goals and objectives.
- **Incident Response & Troubleshooting:**
- Oversee resolution of critical data-related incidents.
- Implement preventative measures for data system reliability.

• *Qualifications:**
- **Experience:** 14+ years in Data Engineering or related roles.
- **Education:** Bachelor's or Master's degree in Computer Science or related field.
- **Cloud Platforms:** Proficiency in AWS, GCP, Azure and their data services.
- **Big Data Technologies:** Expertise in Apache Spark, Hadoop, Kafka, etc.
- **Data Warehousing & Data Lakes:** Experience with Snowflake, Redshift, BigQuery, etc.
- **Programming & Scripting:** Strong skills in Python, Scala, Java, SQL.
- **ETL/ELT & Data Integration:** Extensive experience in building ETL pipelines.
- **Data Modeling:** Mastery of dimensional and relational modeling.
- **Databases:** Understanding of SQL and NoSQL databases.
- **Infrastructure as Code (IaC):** Familiarity with IaC tools for data infrastructure management.
- **DevOps/DataOps/MLOps:** Experience with automated data deployment practices.
- **Communication & Leadership:** Exceptional communication and leadership skills.

In this role, you will have the opportunity to contribute to transforming finance, exploring innovative data solutions, and leading a team of data experts at Goldman Sachs. As a Vice President - Core Engineering (Data Architect) at Goldman Sachs, you will play a crucial role in defining, designing, and overseeing the implementation of enterprise-level data strategies, architectures, and solutions. Your responsibilities will include leading the development and execution of the organization's data strategy, architecting highly scalable data pipelines, ensuring data governance and quality, and providing technical leadership to cross-functional teams.

• *Key Responsibilities:**

- **Strategic Data Architecture & Roadmapping:**
- Lead the development of the organization's data strategy and architectural roadmap.
- Define data governance frameworks, data modeling, and real-time data platforms.
- **Complex Data System Design & Implementation:**
- Architect highly scalable data pipelines for large-scale data processing.
- Select appropriate technologies and patterns for data ingestion and storage.
- **Data Governance & Quality Leadership:**
- Implement data governance policies to ensure data quality and compliance.
- Design and maintain data catalogs and metadata management.
- **Advanced Data Modeling & Database Design:**
- Design and optimize data models for various data stores.
- Ensure performance, scalability, and flexibility in database design.
- **Technology Evaluation & Adoption:**
- Evaluate emerging data technologies and recommend their adoption.
- Drive innovation and efficiency within the data landscape.
- **Performance Optimization & Scalability:**
- Identify and resolve data-related performance bottlenecks.
- Ensure optimal performance and scalability o