OUR MISSION
At Simply Wall St, we help people become confident, long-term investors. The stock market offers an exceptional opportunity for building wealth, but it’s easy to fail. While many chase quick wins, we believe in thinking long-term and investing like a business shareholder. Our product gives individual investors the capabilities to build a portfolio, previously only available to professionals.
WHY JOIN?
Help us empower individuals by giving them a new way to invest in stocks;
Work at a profitable, global, B2C SaaS startup;
Operating at scale with 6.5 million users across 180 countries;
Small team and flexible working environment;
Work with a product customers love: 4.5* Trustpilot Reviews;
Strong employee retention with 70% of the team with us for \>2 years.
See more information about the company, how we work and benefits etc https://simplywallst.atlassian.net/wiki/spaces/SWSP/overview
Simply Wall St is on a mission to help individual investors make better-informed decisions by providing them with the tools and data they need. Our Data Engineering Team is integral to this mission, ensuring that our platform stays ahead of the curve with cutting-edge technology and data analysis.
Problems We are Solving
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Automating detailed equity analysis to provide real-time news insights for our users.
Creating robust data pipelines and web scraping systems to process equity and financial data.
Integrating various data sources, including Capital IQ and web crawled data into our systems.
Developing algorithms and models that provide in-depth portfolio and valuation news analysis.
Your Role
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Design, build, and maintain data pipelines and Python batch jobs.
Turn equity research and analysis into automated systems and tools for individual investors.
Develop systems to process and present data from Capital IQ on our stock investing tool.
Create automated systems for equity news analysis across multiple industries.
Collaborate closely with other team members to ensure our data systems are reliable, scalable, and efficient.
Our Technical Setup
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Languages \& Tools: We mainly use Python and SQL.
Databases: PostgreSQL for application databases and Snowflake data warehouse for processing financial data.
Data Processing: We use dbt and Python for data processing and cloud Python notebooks for analysis and prototyping.
Data Source: Primarily Capital IQ for financial data. Experience processing web-crawled data is very welcome.
About You
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Proficiency in Python and SQL with a strong understanding of best practices in software engineering.
In-depth knowledge of equity markets, stock analysis, and financial valuation principles.
Proven experience in coding financial analysis, ideally within equity research.
Bachelor’s degree in Finance, Computer Science, Mathematics, or related fields.
Solid understanding of financial reports and accounting principles.
Experienced in building and managing data pipelines.
Motivated by solving complex problems and delivering real value to investors.
Nice to Haves
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Experience with dbt for data transformation.
Prior experience in building scalable Python backend systems.
Experience working with Machine Learning/Artificial Intelligence.
Familiar with handling financial data from sources like Capital IQ.
PERKS
Flexible Remote Working: Work where you are most productive;
Simply Stop: Time is one of the most valuable commodities, so we stop working early on Fridays;
Share Club: We provide a subscription to SWS, cash for you to invest \& regular sessions to discuss stocks and investment ideas;
Parental Leave Policy: With a supportive return to work option;
Learning \& Development Fund: We invest in your growth;
Team Events \& Hackathons: An opportunity for everyone to come together and push what is possible.