Goldman Sachs
Data Engineering - Master Data Architecture - Software Engineer - Associate - Da
Goldman Sachs, Dallas, Texas, United States, 75215
Overview
Join to apply for the Data Engineering - Master Data Architecture - Software Engineer - Associate - Dallas role at Goldman Sachs. Goldman Sachs engineers solve challenging problems at scale, building massively scalable software and systems, architecting low latency infrastructure, guarding against cyber threats, and leveraging machine learning to turn data into action. What We Do
At Goldman Sachs, our Engineers don't just make things – we make things possible. Change the world by connecting people and capital with ideas. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets. About Data Engineering
Data plays a critical role in every facet of the Goldman Sachs business. The Data Engineering group focuses on providing the platform, processes, and governance for availability of clean, organized, and impactful data to scale, streamline, and empower our core businesses. The team offers Legend, a comprehensive data platform with a full data modeling environment and data access controls, plus value-add products to help business users operate more efficiently. Engineers build data solutions that source, curate, and distribute critical data to our businesses, including financial product, pricing, transaction, and client reference data. We collaborate with the business to design and curate data models and transform and distribute data for optimal storage and retrieval. Who We Look For
Goldman Sachs Engineers are innovators and problem-solvers who thrive in a fast-paced global environment. We look for creative collaborators who evolve, adapt to change and deliver results. Role: Full-stack Software Engineer, Data Engineering
As a Full-stack Software Engineer on the Data Engineering team, you will help improve the Legend data platform, our curated data offerings, and how the business uses data. Responsibilities include tackling complex engineering problems across distributed software development, optimizing data access and delivery, enabling core access controls via security paradigms, building UIs for data visualization, applying machine learning to curate data, and engaging with businesses to meet data needs. How You Will Fulfill York Potential
Design & develop modern data management tools to curate key data sets, models, and processes, while identifying areas for automation and efficiency Contribute to an open-source technology - https://github.com/finos/legend Drive adoption of cloud technology for data processing and warehousing Engage with data consumers and producers to design appropriate models to enable the business Relevant Technologies
Java, Python, AWS, React Basic Qualifications
A Bachelor or Master degree in a computational field (Computer Science, Applied Mathematics, Engineering, or related quantitative discipline) 2-7+ years of relevant work experience in a team-focused environment 2-7+ years of experience in distributed system design 2-7+ years of experience using Java, Python, and/or React 2-7+ years of experience or interest in functional programming languages Strong object-oriented design and programming skills (Java) Strong experience with cloud infrastructure (AWS, Azure, or GCP) and infrastructure as code (Terraform, CloudFormation, or ARM templates) Proven experience applying domain-driven design to build complex business applications Deep understanding of data curation and data quality, including traceability, security, performance latency, and correctness across supply and demand processes Knowledge of relational and columnar SQL databases, including database design Expertise in data warehousing concepts (e.g., star schema, SQL vs NoSQL modeling, milestoning, indexing, partitioning) Experience in REST and/or GraphQL Experience in creating Spark jobs for data transformation and aggregation Comfort with Agile operating models (Scrum/Kanban) General knowledge of business processes, data flows, and the quantitative models that generate or consume data Excellent communication skills and ability to work with subject matter experts to extract critical business concepts Independent thinker, willing to engage, challenge or learn Ability to stay commercially focused and push for quantifiable commercial impact Strong work ethic, ownership, and urgency Strong analytical and problem-solving skills Establish trusted partnerships with key contacts and users across business and engineering teams Preferred Qualifications
Financial Services industry experience Experience with Pure/Legend Working knowledge of open-source tools such as AWS Lambda, Prometheus Employment type: Full-time | Seniority level: Associate | Job function: Engineering and Information Technology Note: This description preserves the core responsibilities and qualifications for the role as described in the source material.
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Join to apply for the Data Engineering - Master Data Architecture - Software Engineer - Associate - Dallas role at Goldman Sachs. Goldman Sachs engineers solve challenging problems at scale, building massively scalable software and systems, architecting low latency infrastructure, guarding against cyber threats, and leveraging machine learning to turn data into action. What We Do
At Goldman Sachs, our Engineers don't just make things – we make things possible. Change the world by connecting people and capital with ideas. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets. About Data Engineering
Data plays a critical role in every facet of the Goldman Sachs business. The Data Engineering group focuses on providing the platform, processes, and governance for availability of clean, organized, and impactful data to scale, streamline, and empower our core businesses. The team offers Legend, a comprehensive data platform with a full data modeling environment and data access controls, plus value-add products to help business users operate more efficiently. Engineers build data solutions that source, curate, and distribute critical data to our businesses, including financial product, pricing, transaction, and client reference data. We collaborate with the business to design and curate data models and transform and distribute data for optimal storage and retrieval. Who We Look For
Goldman Sachs Engineers are innovators and problem-solvers who thrive in a fast-paced global environment. We look for creative collaborators who evolve, adapt to change and deliver results. Role: Full-stack Software Engineer, Data Engineering
As a Full-stack Software Engineer on the Data Engineering team, you will help improve the Legend data platform, our curated data offerings, and how the business uses data. Responsibilities include tackling complex engineering problems across distributed software development, optimizing data access and delivery, enabling core access controls via security paradigms, building UIs for data visualization, applying machine learning to curate data, and engaging with businesses to meet data needs. How You Will Fulfill York Potential
Design & develop modern data management tools to curate key data sets, models, and processes, while identifying areas for automation and efficiency Contribute to an open-source technology - https://github.com/finos/legend Drive adoption of cloud technology for data processing and warehousing Engage with data consumers and producers to design appropriate models to enable the business Relevant Technologies
Java, Python, AWS, React Basic Qualifications
A Bachelor or Master degree in a computational field (Computer Science, Applied Mathematics, Engineering, or related quantitative discipline) 2-7+ years of relevant work experience in a team-focused environment 2-7+ years of experience in distributed system design 2-7+ years of experience using Java, Python, and/or React 2-7+ years of experience or interest in functional programming languages Strong object-oriented design and programming skills (Java) Strong experience with cloud infrastructure (AWS, Azure, or GCP) and infrastructure as code (Terraform, CloudFormation, or ARM templates) Proven experience applying domain-driven design to build complex business applications Deep understanding of data curation and data quality, including traceability, security, performance latency, and correctness across supply and demand processes Knowledge of relational and columnar SQL databases, including database design Expertise in data warehousing concepts (e.g., star schema, SQL vs NoSQL modeling, milestoning, indexing, partitioning) Experience in REST and/or GraphQL Experience in creating Spark jobs for data transformation and aggregation Comfort with Agile operating models (Scrum/Kanban) General knowledge of business processes, data flows, and the quantitative models that generate or consume data Excellent communication skills and ability to work with subject matter experts to extract critical business concepts Independent thinker, willing to engage, challenge or learn Ability to stay commercially focused and push for quantifiable commercial impact Strong work ethic, ownership, and urgency Strong analytical and problem-solving skills Establish trusted partnerships with key contacts and users across business and engineering teams Preferred Qualifications
Financial Services industry experience Experience with Pure/Legend Working knowledge of open-source tools such as AWS Lambda, Prometheus Employment type: Full-time | Seniority level: Associate | Job function: Engineering and Information Technology Note: This description preserves the core responsibilities and qualifications for the role as described in the source material.
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