Data Engineering

1 - 5 years

0 Lacs

Posted:2 days ago| Platform: Shine logo

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Work Mode

On-site

Job Type

Full Time

Job Description

At Goldman Sachs, our Engineers don't just make things - we make things possible. We change the world by connecting people and capital with ideas, solving the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets. Engineering, which is comprised of our Technology Division and global strategists groups, is at the critical center of our business. Our dynamic environment requires innovative strategic thinking and immediate, real solutions. If you want to push the limit of digital possibilities, start here. Goldman Sachs Engineers are innovators and problem-solvers, building solutions in risk management, big data, mobile, and more. We look for creative collaborators who evolve, adapt to change, and thrive in a fast-paced global environment. Data plays a critical role in every facet of the Goldman Sachs business. The Data Engineering group is at the core of that offering, focusing on providing the platform, processes, and governance for enabling the availability of clean, organized, and impactful data to scale, streamline, and empower our core businesses. As a Site Reliability Engineer (SRE) on the Data Engineering team, you will be responsible for observability, cost, and capacity with operational accountability for some of Goldman Sachs's largest data platforms. We engage in the full lifecycle of platforms from design to demise with an adapted SRE strategy to the lifecycle. We are looking for individuals with a background as a developer who can express themselves in code. You should have a focus on Reliability, Observability, Capacity Management, DevOps, and SDLC (Software Development Lifecycle). As a self-leader comfortable with problem statements, you should structure them into data-driven deliverables. You will drive strategy with skin in the game, participate in the team's activities, drive Postmortems, and have an attitude that the problem stops with you. **How You Will Fulfil Your Potential** - Drive adoption of cloud technology for data processing and warehousing - Drive SRE strategy for some of GS's largest platforms including Lakehouse and Data Lake - Engage with data consumers and producers to match reliability and cost requirements - Drive strategy with data **Relevant Technologies**: Snowflake, AWS, Grafana, PromQL, Python, Java, Open Telemetry, Gitlab **Basic Qualifications** - A Bachelor's or Master's degree in a computational field (Computer Science, Applied Mathematics, Engineering, or in a related quantitative discipline) - 1-4+ years of relevant work experience in a team-focused environment - 1-2 years hands-on developer experience at some point in career - Understanding and experience of DevOps and SRE principles and automation, managing technical and operational risk - Experience with cloud infrastructure (AWS, Azure, or GCP) - Proven experience in driving strategy with data - Deep understanding of multi-dimensionality of data, data curation, and data quality - In-depth knowledge of relational and columnar SQL databases, including database design - Expertise in data warehousing concepts - Excellent communication skills - Independent thinker, willing to engage, challenge, or learn - Ability to stay commercially focused and to always push for quantifiable commercial impact - Strong work ethic, a sense of ownership and urgency - Strong analytical and problem-solving skills - Ability to build trusted partnerships with key contacts and users across business and engineering teams **Preferred Qualifications** - Understanding of Data Lake / Lakehouse technologies incl. Apache Iceberg - Experience with cloud databases (e.g., Snowflake, Big Query) - Understanding concepts of data modeling - Working knowledge of open-source tools such as AWS lambda, Prometheus - Experience coding in Java or Python,

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Goldman Sachs

Financial Services

New York

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