Analytics Engineer

Swish Analytics • San Francisco, CA

13h

About The Position

Swish Analytics is hiring an Analytics Engineer for its Suspensions team. The team develops and operates the framework, monitoring, and analysis for suspending and resuming markets, from pregame opening through live gameplay and close. Its work includes real-time event processing triggered by live game state, monitoring suspension and resumption latency and failures, tools for reconstructing and auditing suspension events, and rate and downtime metrics for evaluating suspension coverage across sports and markets.

The role combines hands-on analysis of raw production data and systems with software engineering. The engineer investigates incidents, develops statistical measures and stakeholder reporting, improves the team's framework and tooling, and explains system behavior using real-time, event-driven data. The team works in Python and Rust and partners with data science, trading, and engineering teams. The position requires the ability to independently drive ambiguous problems to resolution.

Requirements

• Bachelor's degree in Computer Science, Statistics, Data Science, or a similar major.
• At least 4 years of professional software engineering experience, including production systems.
• At least 2 years of Python experience, including data extraction, wrangling, and analysis.
• At least 1 year of Rust experience in a production environment.
• Experience building and maintaining software that runs in production against real-world data, rather than only prototypes, one-off scripts, or notebook-based analysis.
• Strong SQL skills and direct experience working with raw or source data such as logs, event streams, and production tables.
• Experience taking on open-ended problems with limited upfront direction, identifying questions and collaborators, and driving work to completion without a pre-scoped problem.
• Statistical and quantitative reasoning skills, including the ability to build rigorous, defensible measures of system behavior.

Nice To Haves

• Experience with event-driven or real-time data systems, such as Kafka or comparable systems.
• Background in analytics engineering, applied statistics, or a hybrid data/software role.
• Exposure to sports, sports betting, or trading concepts.

Responsibilities

• Investigate individual incidents and requests end-to-end using raw production data and systems to determine root causes and recommend resolutions.
• Build and maintain metrics measuring system health and performance over time, using statistical methods as the core analytical approach, and produce clear descriptive reporting for stakeholders.
• Contribute to the team's core framework and tooling so investigation and measurement work becomes more repeatable and less bespoke.
• Work independently on ambiguous, partially scoped problems and identify cross-functional partners, including data science, engineering, and trading, when needed.
• Use real-time, event-driven data to reconstruct and explain system behavior during live events.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior