A bit about us:
Our client is a venture-backed and founder-led global corporate data provider and commercial intelligence platform, serving financial institutions, legal & advisory service providers, multinationals, journalists, and governments. They are building world-class SaaS products that help our clients glean insights from vast datasets that we collect, extract, enrich, match and analyze using a highly scalable data pipeline. From financial intelligence to anti-counterfeiting, and from free trade zones to war zones, they power cross-border and cross-lingual insight into customers, counter-parties, and competitors. Thousands of analysts and investigators in over 30 countries rely on our products to safely conduct cross-border trade, research front-page news stories, confidently enter new markets, and prevent financial crimes such as corruption and money laundering.
Why join us?
- Limitless growth and learning opportunities
- A collaborative and positive culture - your team will be as smart and driven as you
- A strong commitment to diversity, equity & inclusion
- Exceedingly generous vacation leave, parental leave, floating holidays, flexible schedule, & other remarkable benefits
- Outstanding competitive compensation & commission package
- Comprehensive family-friendly health benefits, including full healthcare coverage plans, commuter benefits, & 401K matching
You will help to harvest and transform hundreds of millions of structured and unstructured records from over 150 countries and 30 languages into a dynamic and meaningful graph of entities and relationships. You will also work with data and analytics experts and analysts to find and resolve data quality problem.
- Three plus years of experience developing in Python (e.g. pandas, NumPy, Scrapy)
- Ability to create and maintain complex SQL queries
- Familiarity with graph databases
- Conduct exploratory data analysis and data visualization for generating and reporting key performance indicators to relevant stakeholders
- Comfortable working in a cloud environment (GCP/AWS)
- Familiar with data warehousing best practices
- Experience in data warehousing, test planning, writing and executing test cases, and creating automation scripts for ETL testing
- Familiar with developing and deploying containerized applications and services, including orchestration, particularly Kubernetes