Manager, Data Analytics and Engineering

PrizePicks · Remote, United States

At PrizePicks, we are the fastest-growing sports company in North America, as recognized by Inc. As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues, including the NFL, NBA, and Esports titles like League of Legends and Counter-Strike. Our team of over 550 employees thrives in an inclusive culture that values individuals from diverse backgrounds, regardless of their level of sports fandom. We are looking for a

Data and Analytics Engineering Manager

to lead a team responsible for building and operating scalable, reliable, and high-quality data engineering pipelines producing analytical data products. This role blends people leadership, technical stewardship, and cross-functional collaboration to ensure data is trusted, accessible, and delivered in support of analytics, AI, and business decision-making.
You will manage a team of data engineers, set technical direction, and partner closely with Product, Analytics, Infrastructure, and Business stakeholders to deliver high-impact data solutions.
Lead, mentor, and develop a team of Data Engineers through regular 1:1s, coaching, and performance feedback
Own hiring, onboarding, career development, and performance management for the team
Own the design, development, and operation of data ingestion, transformation, storage pipelines (batch and streaming), and analytical model(s)
Ensure reliability, scalability, performance, and cost efficiency of data systems
Drive best practices in data modeling, data quality, observability, and operational excellence
Review and guide technical designs, architecture decisions, and code quality
Partner with platform and infrastructure teams on tooling, security, and scalability
Partner with Product, Analytics Engineering, Data Science, and Business teams to deliver trusted datasets and metrics
Communicate progress, risks, and tradeoffs clearly to stakeholders and leadership
Establish and enforce data engineering standards, patterns, and documentation
Support data governance, data contracts, and schema management
Ensure compliance with security, privacy, and data retention requirements
A graduate degree in Computer Science, Mathematics, or a related quantitative field.
~8+ years of experience in Data Engineering or related roles
~3+ years leading engineers (hiring, coaching, delivery accountability).
~ Strong distributed systems fundamentals (scaling, reliability, data correctness).
~ Hands-on ability in

Python and/or Java

(can dive into code and unblock delivery).
~ Experience with cloud data ecosystems (GCP - Preferred, AWS, or Azure)
~ Proficiency with

SQL

and at least one programming language (Python, Java, or Scala)
~ Solid understanding of

data modeling, ETL/ELT

patterns, and data reliability
~ Experience with modern

data warehouses / lakehouses

(BigQuery, Snowflake, Redshift, Iceberg)
~ Familiarity with analytics engineering tools ( dbt, semantic layers )
~ Exposure to data governance, observability, and data quality tooling
~ Quality-first:

designs for operability, correctness, and reliability from day one.

S. and are willing to consider remote candidates. #LI-Remote

Your recruiter will be happy to chat more about the specific pay range for your location and how we arrived at it during the hiring process.
This application period will remain open for 30 days. In addition to your great compensation package, full-time employees will be eligible for the following perks:

~ Company-subsidized medical, dental, & vision plans
~Annual bonus
~ Flexible PTO to encourage a healthy work/life balance (2 weeks STRONGLY encouraged!)
~ Generous paid leave programs, including 16-week paid parental leave and disability benefits
~ Company equipment provided (Windows & Mac options)
~ Annual performance reviews with opportunities for growth and career development

We are unable to sponsor or take over sponsorship of an employment Visa at this time.
All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.