Manager, Data Analytics and Engineering

At PrizePicks, we are the fastest-growing sports company in North America, as recognized by Inc. 5000. 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. Ready to reimagine the DFS industry together? 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. What you’ll do: 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.

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 What you have: - 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) - 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 - Self-starter + ownership: drives ambiguous problems to durable solutions. - Builds and grows teams: mentors, raises the bar, and develops talent. - Quality-first: designs for operability, correctness, and reliability from day one.