Data Engineer - Measurement - Tech Risk
MORE ABOUT THIS JOB Business Unit Overview
Led by the Chief Information Security Officer (CISO), Technology Risk secures Goldman Sachs against hackers and other cyber threats. We are responsible for detecting and preventing attempted cyber intrusions against the firm, helping the firm develop more secure applications and infrastructure, developing software in support of our efforts, measuring cybersecurity risk, and designing and driving implementation of cybersecurity controls. The team has global presence across the Americas, APAC, India and EMEA. Within Technology Risk, Tech Risk Engineering creates targeted solutions to solve thematic control gaps across the firm. We are a team of security, software, and data engineers that identify and curate technology data, provide technology solutions in the threat management space, and drive real-time response processes to meet regulatory and management requirements. We build exciting, novel solutions and identify gaps to bridge platforms across Core Engineering. The Security Engineering team within Tech Risk is responsible for building services and platforms that interact with the Software Development Life Cycle processes at Goldman Sachs to provide security related checks, policy controls and associated reporting. Role
The Measurement engineering team follows a data driven approach to build-out auto-measurements to valid audit critical IT general controls (ITGC) and beyond. As a member of Measurement engineering, you will be part of a team that is responsible for designing, building, and managing data infrastructures to delivery and process large datasets from a variety of data platforms including but not limited to RDBMS, NoSQL, Data lake, Public cloud, etc. The ideal candidate must be able to deal with ambiguity as they collaborate with the business users to understand the business objectives, drive requirements and develop auto-measurement metrics (data refiners) on an in-house platform using Spark and Scala RESPONSIBILITIES AND QUALIFICATIONS Qualifications
ABOUT GOLDMAN SACHS
- Knowledge of data management fundamentals and data storage principles
- Knowledge of distributed systems as it pertains to data storage and computing
- Advanced working SQL knowledge and experience with optimizing SQL across large datasets
- Experience in building and optimizing 'big data' data pipelines, architectures and datasets.
- Experience with big data tools: Hadoop, Spark, Kafka, etc. but not necessary the exact named-software
- Experience in building processes supporting: data extraction/ingestion, data transformation and REST APIs
- Knowledge about API design standards, patterns and best-practices especially Swagger and REST, SOAP, JSON, Microservices etc.
- Proficiency in one or more of the following languages - Python, Java, or similar
- Excellent communication (verbal and written) and interpersonal skills, and an ability to effectively communicate with both business and technical teams
The Goldman Sachs Group, Inc. is a leading global investment banking, securities and investment management firm that provides a wide range of financial services to a substantial and diversified client base that includes corporations, financial institutions, governments and individuals. Founded in 1869, the firm is headquartered in New York and maintains offices in all major financial centers around the world.
Â© The Goldman Sachs Group, Inc., 2020. All rights reserved Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Vet.