Job description

Kalshi is defining a new category Kalshi has defined a new category: prediction markets. Kalshi allows people to trade on the outcome of any events and turn any question about the future into a financial asset. Kalshi fought for years and legalized prediction markets in the US for the first time in history. Kalshi is currently the fastest growing financial market in America, and has thousands of markets across politics, economics, financials, weather, tech, AI, culture and more. We believe prediction markets have the potential to be the largest financial market because they turn anything into a financial position. Our vision: well… build the largest financial market on the planet. Our mission: bring more truth to the world through the power of markets. Building a new category is hard… like really hard. But it’s beautiful and deeply fulfilling . Our culture is simple: we hire really talented people, work really hard, and enjoy the climb. We are looking for ambitious and exceptional people to join our (relatively small) team to help us build the next generation of financial markets. Role Roadmap 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. Some of the projects you may work on: 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 Technology: 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. What you’ll do: Partner with backend engineering teams to design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Design and maintain robust ETL processes, focusing on data quality, error handling, and automated monitoring while continuously optimizing performance and resource utilization Work with product teams to identify gaps in our end-to-end data insights workflow and lead engineering efforts to improve it Partner with data scientists to implement and optimize feature engineering pipelines, support experimentation workflows, and build scalable infrastructure for model deployment and training data preparation Build intuitive internal tools and dashboards that enable operations and growth teams to efficiently query and analyze data without requiring deep technical expertise What we’re looking for: Bachelor's degree in Computer Science or equivalent professional experience, with 4+ years of hands-on software development Strong command of key programming languages (Python, Golang, Java) Proven track record in data pipeline development using modern orchestration tools (Airflow, Flink, Dagster) Production experience with real-time data streaming platforms like Apache Kafka and Flink Hands-on expertise with major cloud data warehouses (Snowflake, Redshift) and traditional databases like PostgreSQL Strong data visualization skills using industry-standard tools (Tableau, Superset, Looker) Proven track record of taking initiative and thriving in fast-paced environments Sharp analytical skills with a focus on market dynamics and consumer insights Passionate about your craft and committed to delivering exceptional results Bonus points Spearheaded data engineering initiatives for a high-growth consumer platform, delivering end-to-end data solutions from ingestion to insights Our Culture Meritocracy is at our core, and we value people who take ownership and figure (usually hard) things out. We dream big. We love our craft deeply and are proud of what we put out in the world. We are committed to our vision of building something big… but also useful: a product that brings more truth through the power of markets. Kalshians are Kalshi’s most important asset: we pick Kalshians carefully, so we trust them fully on day 1. NYC Pay Transparency Disclosure: Salary Range: $100,000 to $250,000 annually plus equity and benefits. This salary range is based on the current available market data and represents the expected salary range for this role. Kalshi has minimal hierarchy and few titles, but a broad range of experience is represented within roles. Should you have compensation expectations that exceed these bands, we'd love to hear from you and would welcome you to reach out to discuss further. Commitment to Equal Opportunity Kalshi is committed to creating a culture of inclusion and belonging, and we are proud to be an equal opportunity employer. We believe it is our collective responsibility to uphold these values and encourage candidates from all backgrounds to join us in our mission. All qualified applicants will be treated with respect and receive equal consideration for employment without regard to race, color, creed, religion, sex, gender identity, sexual orientation, national origin, disability, uniform service, veteran status, age, or any other protected characteristic per federal, state, or local law. If you are passionate about what you do and want to use your talents to support our mission and values, we’d love to hear from you.

Requirements

Must-haves

Kalshi is defining a new category
We believe prediction markets have the potential to be the largest financial market because they turn anything into a financial position.
Our vision: well… build the largest financial market on the planet.
Our mission: bring more truth to the world through the power of markets.
Role Roadmap
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.
Some of the projects you may work on:
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
Partner with backend engineering teams to design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse
Design and maintain robust ETL processes, focusing on data quality, error handling, and automated monitoring while continuously optimizing performance and resource utilization
Work with product teams to identify gaps in our end-to-end data insights workflow and lead engineering efforts to improve it
Partner with data scientists to implement and optimize feature engineering pipelines, support experimentation workflows, and build scalable infrastructure for model deployment and training data preparation
Build intuitive internal tools and dashboards that enable operations and growth teams to efficiently query and analyze data without requiring deep technical expertise
Bachelor's degree in Computer Science or equivalent professional experience, with 4+ years of hands-on software development
Strong command of key programming languages (Python, Golang, Java)
Proven track record in data pipeline development using modern orchestration tools (Airflow, Flink, Dagster)
Production experience with real-time data streaming platforms like Apache Kafka and Flink
Hands-on expertise with major cloud data warehouses (Snowflake, Redshift) and traditional databases like PostgreSQL

Nice-to-haves

Spearheaded data engineering initiatives for a high-growth consumer platform, delivering end-to-end data solutions from ingestion to insights

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aigopythonsqlmachine learningawsgolangjava

Platform: greenhouse
Effort: quick

Benefits

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Vision