Data Engineer
Slant|Posted 3 days ago
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Skills and experience
Location and salary
Role description
Join Slant, a fast-growing startup reimagining investment research through alternative data and AI. As our Data Engineer, you'll design and build the scalable data infrastructure that powers insights used by leading investors and corporate executives across South Africa and beyond.
You'll be responsible for developing production-grade ETL/ELT pipelines, maintaining our data warehouse, and creating robust data models that transform raw data into actionable intelligence. Working closely with data science, product, and research teams, you'll optimise complex queries, implement data governance processes, and drive adoption of cutting-edge tools and technologies.
We're looking for someone with around 3 years of experience who brings strong expertise in data warehousing (AWS, BigQuery, Snowflake), advanced SQL skills, and Python proficiency. You'll collaborate directly with our founder to shape company strategy, giving you a front-row seat to decision-making and the opportunity to experiment at the leading edge of AI and alternative data in finance.
Our startup culture values experimentation, accountability, and continuous learning, making this ideal for self-starters who thrive in fast-changing environments. We offer profit participation so you can share directly in the company's growth and success. You'll have ownership of critical data infrastructure, flexible working hours, and a hybrid work setup in Cape Town. This is your chance to build something meaningful while working in a supportive environment focused on product excellence and continual learning.
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About Slant
What we do
Slant is a research-led market analytics company that turns real consumer transaction data into intelligence for investors and consumer-facing businesses. Each month we process 250,000 anonymised South African bank accounts - roughly 25 million transactions - covering all major banks. Every transaction is classified against our proprietary brand and retailer taxonomy, giving clients a granular, observed view of how money is actually being spent across the economy. We deliver this through interactive dashboards, bespoke research, and a monthly publication, Currents, that synthesises emerging consumer trends. Our clients include leading retailers, asset managers, and corporate strategy teams.
Why work for us
Slant sits on one of the most distinctive datasets in South African finance: millions of real consumer transactions, updated weekly, spanning every major spending category. You won't be working with surveys or scraped proxies - you'll be building models and products on observed behaviour. As a small, growing team you'll have direct access to leadership, real ownership of what you build, and the ability to see your work shape investment decisions and corporate strategy.
Our culture
We are a small team that values rigour, curiosity, and clear thinking. The work is research-driven - we believe that the quality of insight depends on the depth of engagement with the data. We operate with minimal hierarchy: ideas are tested on merit, feedback is direct, and everyone contributes to the direction of the product. We're looking for people who take ownership and pride in delivering excellence for clients.
Our data process
Our stack is built on Python, SQL, AWS, and BigQuery. The core technical challenge is categorising and enriching millions of raw transactions into structured, brand-level market intelligence - then making that data available to clients through dashboards and research products. We work iteratively, shipping frequently and refining based on what we learn. We're actively expanding our use of ML and LLMs to improve classification, segmentation, and insight generation.
Our hiring process
Our process is straightforward and designed around mutual fit. It typically includes an initial conversation with the founder, a technical assessment relevant to the role, and a team interview. We move quickly and value directness throughout.
Tech Stack
application and data
dev ops
business tool
utilities
