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# Staff Analytics Engineer

- **Company:** FanDuel Inc
- **Location:** New York, United States
- **Experience:** Experienced
- **Salary:** $159,000.0 - $199,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon S3, Data Analysis, Command-Line Interface, Data Cleansing, Information Engineering, Web Scraping, Data Transformation, Data Stores, Relational Databases, Software Design Patterns, R (Programming Language), Python (Programming Language), Operational Databases, Standard Sql, SQL Databases, Tableau (Software), Data Lakes, Data Pipelines, Databricks
- **Published:** October 28, 2026
- **Apply:** https://startup.jobs/staff-analytics-engineer-fanduel-10591624

## About the Role

* 7+ years of experience working in an analytics/data engineering role, including senior or lead-level responsibilities
 * 4+ years designing and maintaining databases and data ingestion pipelines, ideally including real-time ingestion and web scraping
 * Deep understanding of relational databases
 * Proficient in SQL, Databricks, R/Python, Tableau, AWS s3 buckets, command line
 * Proven experience building production data pipelines with Python/R and Databricks, and hands-on experience designing medallion (bronze/silver/gold) or comparable layered architectures
 * Bachelor's Degree, preferably in a highly numerate major (Math, Stats, Econ, etc.) or relevant experience in data analysis role
 * Strong personal organizational and time management skills
 * Ability to work in a fast-paced environment
 * Strong problem-solving skills
 * Demonstrated experience mentoring engineers and elevating a team's technical best practices, standards, and ways of working
 * Comfort operating with ambiguity in a scrappy, early-stage build, making sound architecture and prioritization decisions with incomplete information
 * Exposure to sports data (NBA/NFL, and especially international soccer) is a strong plus

## Description

As a Staff Analytics Engineer for our Sports Modeling & Innovation team, you will be a senior technical leader on a global data initiative focused on expanding and improving the auxiliary data that can be joined to our customer bet data. You will set the technical direction for how we source, ingest, model, and serve new data assets, and you will be responsible for designing, building, and scaling the data models, pipelines, and architecture that power business performance impacting decisions for data scientists, analysts, and traders.

The first year of this work will be scrappy and hands-on, spanning real-time data ingestion, building scrapers, and standing up a medallion architecture from the ground up. We will start with NBA and NFL, which have relatively solid data foundations, before pivoting to an international soccer model that will require a significantly heavier lift. Beyond the build, you will be expected to raise the bar for the broader team, mentoring other analytics engineers and driving improvements to our engineering best practices, standards, and ways of working. This is a great opportunity for a seasoned engineer who thrives in an environment where curiosity is rewarded and people are empowered to make decisions. The ideal candidate will have a passion for learning, a bias toward action, and a desire to shape how we leverage our data at scale.

In addition to the specific responsibilities outlined above, employees may be required to perform other such duties as assigned by the Company. This ensures operational flexibility and allows the Company to meet evolving business needs.

THE GAME PLAN
Everyone on our team has a part to play

 * Architecting and building pipelines for fast (often real-time) ingestion of auxiliary data into well-designed data stores (SQL, Delta Lake, medallion architecture), including standing up new sources from scratch
 * Building and maintaining scrapers and validation pipelines that source new external data, flag bad or missing data, and evolve as new datasets and sports come online
 * Own the design and delivery of the medallion architecture and data transformation jobs for the global data project, setting standards for the codebase and troubleshooting complex issues across the stack
 * Establish scalable approaches to database management and automated data cleaning across large, messy, and heterogeneous datasets
 * Make decisions between memory and speed tradeoffs to best optimize team's project needs - help reduce query execution times where possible and remove unnecessary/unused metrics
 * Partner with stakeholders to prioritize and deliver the data products (curated datasets, Tableau dashboards, R Shiny apps) built on top of the new auxiliary data
 * Mentor other analytics engineers, lead by example, and drive adoption of best practices, coding standards, and design patterns across the team
 * Influence technical strategy and roadmap for the global data project, making pragmatic build-vs-buy and architecture decisions in a fast-moving, ambiguous environment
 * Curiosity about AI and emerging technologies is a plus