Data Engineer, Kalshi

• We are looking for intellectually curious, highly motivated individuals to be foundational members of our Data team!
• You should have strong critical thinking and analytical skills, excellent communication abilities, and a knack for working across teams in a fast-paced environment
• The ideal candidate will be adept in navigating the data stack and able to support initiatives in all facets from analytics/data engineering and product analytics
• Expertise in Python and SQL with a strong familiarity with Pandas, Numpy, DBT,
• Knowledge of Big Data tools like Spark is preferred
• Experience with cloud platforms (bonus points for AWS)
• Expertise in data visualization tools and BI tools
• Intermediate understanding of Machine Learning algorithms and principles
• Extremely strong statistical analysis skills
• Ability to lead initiatives across multiple product areas and communicate findings with leadership and product teams
• 3+ years of Data Engineering experience
• Love what Kalshi is building
• Ownership mentality
• Excellent verbal communications, including the ability to clearly and concisely articulate complex concepts to both technical and non-technical collaborators
• Can manage ambiguity and working on multiple projects at once

Desirable

• As our go to data person at Kalshi, you build and operate the full data stack at Kalshi
• This role is one part data engineering, one part data analysis
• Partner closely across the business to find improvements/opportunities and influence decisions using data science methodologies and tools
• Drive the collection of new data and the refinement of existing data sources and pipelines
• Build actionable KPIs, create production-quality dashboards and notebooks to convey insights
• Analyze large, complex datasets to extract insights and decide on the appropriate techniques and data representation
• Define and advance best practices within an experiment-driven culture
• Inform product engineering roadmap through analysis of marketplace, user behavior, and product trends
• Our tech stack includes Python, SQL, DBT for data analytics and pipelining, pipelining and machine learning, Spark for big data processing, and visualization through Superset. We leverage cloud platforms such as AWS for scalable data storage and computational needs
• You will partner with our Engineering and Product teams to identify critical goals for the business, develop a deep understanding of them, and design scalable solutions