Manager, Data Analytics and Engineering

About PrizePicks

PrizePicks is the fastest-growing sports company in North America, as recognized by Inc. 5000, and 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.

Overview

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.

Responsibilities

People & Team Leadership

• 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.
• Foster a culture of accountability, ownership, collaboration, and continuous improvement.
• Balance delivery expectations with sustainable team practices.

Technical & Delivery Ownership

• 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.

Execution & Stakeholder Collaboration

• Translate business and analytics requirements into scalable technical solutions.
• Partner with Product, Analytics Engineering, Data Science, and Business teams to deliver trusted datasets and metrics.
• Own sprint planning, prioritization, and delivery commitments.
• Communicate progress, risks, and tradeoffs clearly to stakeholders and leadership.

Governance & Standards

• 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.

Qualifications

• 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.
• Proficiency with SQL and at least one programming language (Python, Java, or Scala).
• Experience with cloud data ecosystems (GCP preferred, AWS, or Azure).
• Experience with orchestration tools (Airflow, Argo, etc.).
• Solid understanding of data modeling, ETL/ELT patterns, and data reliability.
• Experience with streaming technologies (Kafka, Flink, Spark Streaming).
• 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.