Vice President Core Engineering (Data Architect)

As a Senior Data Engineer / Data Architect at Goldman Sachs, you will be a technical leader and subject matter expert responsible for defining, designing, and overseeing the implementation of enterprise-level data strategies, architectures, and solutions. Your role will involve managing complex data environments, aligning data initiatives with business objectives, and leading cross-functional teams to foster a data-driven culture. You will ensure data integrity, accessibility, security, and compliance across the organization's data assets. **Key Responsibilities:** - Lead the development and execution of the organization's data strategy and architectural roadmap, including data governance frameworks, data modeling, data warehousing, data lakes, and real-time data platforms. - Architect and design highly scalable, robust, and fault-tolerant data pipelines and platforms for large-scale data ingestion, processing, storage, and consumption. - Define and implement comprehensive data governance policies, standards, and best practices to ensure data quality, consistency, security, privacy, and regulatory compliance. - Lead the design and maintenance of conceptual, logical, and physical data models for various data stores optimizing for performance, scalability, and flexibility. - Continuously evaluate emerging data technologies, tools, and industry trends to recommend and lead their adoption, driving innovation and efficiency within the data landscape. - Proactively identify and resolve complex data-related performance bottlenecks to ensure optimal performance and scalability of data platforms and solutions. - Provide expert technical guidance, mentorship, and leadership to data engineering and analytics teams, fostering best practices in data architecture development and operational excellence. - Collaborate extensively with business stakeholders, product teams, software engineers, and IT operations to translate complex business requirements into effective data solutions and ensure alignment with organizational goals. - Oversee the resolution of critical data-related incidents, perform root cause analysis, and implement preventative measures to ensure high availability and reliability of data systems. **Qualifications:** - Experience: 14 years of progressive experience in Data Engineering, Data Architecture, or related roles with a strong focus on designing and implementing large-scale enterprise-level data solutions. - Education: Bachelors or Masters degree in Computer Science, Software Engineering, Information Technology, or a related quantitative field. - Cloud Platforms: Expert-level proficiency and extensive hands-on experience with major cloud providers (e.g. AWS, GCP, Azure) and their data services. - Big Data Technologies: Deep expertise in big data technologies such as Apache Spark, Hadoop, Kafka, and distributed processing systems. - Data Warehousing & Data Lakes: Proven experience with data warehousing and data lake/lakehouse architectures. - Programming & Scripting: Strong programming skills in languages commonly used in data engineering (e.g. Python, Scala, Java, SQL). - ETL/ELT & Data Integration: Extensive experience in designing, building, and optimizing complex ETL/ELT pipelines and data integration processes. - Data Modeling: Mastery of various data modeling techniques and tools. - Databases: Strong understanding of various database technologies (SQL and NoSQL) and data platforms. - Infrastructure as Code (IaC): Familiarity with IaC tools for managing data infrastructure. - DevOps/DataOps/MLOps: Understanding and experience with DevOps, DataOps, and MLOps principles and practices. - Communication & Leadership: Exceptional communication, presentation, and interpersonal skills with a proven ability to influence stakeholders and lead technical teams. **Preferred Qualifications:** - Experience in specific industry domains (e.g. finance, healthcare, e-commerce). - Certifications in relevant cloud data platforms. - Experience with data visualization tools. - Familiarity with master data management (MDM) and data quality tools. - Understanding of machine learning workflows and MLOps. Goldman Sachs is committed to fostering diversity and inclusion in the workplace and ensuring opportunities for professional and personal growth for all individuals within the firm. Learn more about the culture, benefits, and people at Goldman Sachs. As a Senior Data Engineer / Data Architect at Goldman Sachs, you will be a technical leader and subject matter expert responsible for defining, designing, and overseeing the implementation of enterprise-level data strategies, architectures, and solutions. Your role will involve managing complex data environments, aligning data initiatives with business objectives, and leading cross-functional teams to foster a data-driven culture. You will ensure data integrity, accessibility, security, and compliance across the organization's data assets. **Key Responsibilities:** - Lead