ABOUT FRANCHISE DATA ENGINEERING
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.
Franchise Data Engineering is a team within the Global Banking & Markets (GBM) division responsible for building data pipelines and curating data
specifically for GBM CFO and Capital Management teams. Franchise Data Engineering team design, build and re-engineer scalable and resilient data
solutions that propel the Global Banking & Markets Division’s efforts around PnL analytics and Capital optimization which is leveraged by Division Heads
and Executive Office. Team engages with stakeholders across all business lines of GBM to understand the data, workflows and analyze processes that
are critical for driving strategic commercial outcomes and then develop/iterate on the deployment of high-quality data solutions that empower those efforts.
Our engineers collaborate closely with businesses to ensure their data needs are met and we react quickly to new demands by rapidly evolving our
solutions.
HOW YOU WILL FULFILL YOUR ROLE
The Analyst/Associate Role (1-4 years of experience) involves dynamically collaborating across business and engineering teams, translating
business problems into detailed data specifications and then designing, building and deploying scalable relational data models which would serve
as the source for business user's/consumer's analytical use cases. The role requires end-to-end skills in data engineering, ETL, data modeling,
distributed databases, math/logic and a good grasp SDLC best practices along with Data Governance aspect. In the course of building this data
solution, the engineer will benefit from and be required to learn financial data engineering as it is performed at a top tier financial firm.
SKILLS AND EXPERIENCE WE ARE LOOKING FOR
- Academic Qualifications: A Bachelors or Masters 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 global team-oriented environment
- Strong object-oriented design and hands on experience in one of programming languages (such as Java, Python, C++) using Object Oriented
- design techniques and best practices.
- Deep understanding of multidimensionality of data, data curation and data quality, such as traceability, security, performance latency and
- correctness across supply and demand processes
- In-depth knowledge of relational and columnar SQL databases, including database design
- Expertise in data warehousing concepts (e.g. star schema, entitlement implementations, SQL modeling, milestoning, indexing, partitioning)
- Excellent communications skills and the ability to work with subject matter experts to extract critical business concepts and gather business
- requirements
- 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 collaborate effectively across global teams and communicate complex ideas in a simple manner
PREFERRED QUALIFICATIONS
- Industry Experience in Data engineering.
- Exposure to cloud databases (such as Snowflake, Single Store).
- Exposure to cloud infrastructure (AWS, Azure, or GCP) and infrastructure as code (Terraform).
- Experience with programming for extract transform load (ETL) operations and data analysis.