Analytics & Data Platform Lead

Lucra Sports•New York, NY

3d•Remote

About The Position

Lucra is seeking an Analytics & Data Platform Lead to own, build, and operate our data foundation. This role is responsible for the maintenance and development of our core data stack, ensuring that raw product, financial, and operational data is transformed into reliable, actionable insights that drive business decisions. This is a high-impact individual contributor role with clear ownership and visibility across leadership. The ideal candidate will be hands-on with the full analytics lifecycle — from product instrumentation and data modeling to ad-hoc analysis and executive reporting — while also laying the groundwork for how data will operate strategically at Lucra in the future. The right person is comfortable owning the “messy middle” of data work today: fixing tracking gaps, building dashboards from imperfect inputs, answering urgent business questions, and creating operational reporting that helps teams execute. Over time, this role will evolve the platform, practices, and standards that enable data to become a true strategic advantage across product, sales, operations, and client experience.

Requirements

5+ years of experience in analytics, analytics engineering, or data platform roles
Experience operating in high-growth SaaS environments (Series A–C preferred)
Strong SQL skills and experience modeling analytics data
Proficiency in Python
Experience managing and optimizing Redshift (or a comparable cloud data warehouse like Snowflake, BigQuery)
Familiarity with the tools in our data & analytics stack (Redshift, dbt, Sigma, Segment)
Experience with event tracking implementation, specifically Mixpanel (or a similar event-based analytics platform like Amplitude)

Nice To Haves

Experience as an early or founding data hire
Familiarity with usage-based pricing, marketplaces, or transaction-driven platforms
Exposure to client-facing analytics or data monetization
Experience supporting AI or advanced analytics initiatives
B2B SaaS or platform experience

Responsibilities

Data Foundation & Source of Truth
Ad-Hoc Analysis: Provide comprehensive data support for the team. Conduct deep-dive analyses to uncover trends, identify root causes for changes in both product and operational metrics, and provide data-backed recommendations for strategy. This includes developing and maintaining dashboards for key operational metrics.
Maintain and Govern Data Infrastructure: Serve as the primary dedicated resource for the operational health, performance, and cost-efficiency of our core data stack, including Redshift, dbt (data build tool), and Sigma Computing.
ETL/ELT Pipeline Management: Design, develop, and maintain robust data transformation workflows using dbt to ensure data is clean, modeled, and ready for use by all stakeholders across the organization.
Data Quality & Reliability: Implement and monitor data quality checks, testing, and documentation to ensure accuracy and reliability across all production data models, acting as a steward for our data assets.
Schema & Warehouse Management: Manage the structure and optimization of the Redshift data warehouse, including performance tuning and user access management.
Executive, Board & Finance Analytics
Build and maintain board-ready and executive dashboards
Support revenue realization tracking and forecasting
Develop unit economics and cost-to-serve models (by user, feature, and client)
Partner with Finance on invoicing accuracy, revenue share validation, and margin analysis
Product Analytics, Client & Marketing Insights
Own the administration and configuration of our product analytics tools for segmentation, cohort analysis, and funnel creation.
Deliver actionable insights into product adoption, engagement, and retention
Support experimentation frameworks and post-launch monitoring
Partner with Client Success to develop client health, renewal, and upsell signals
Enable Sales and Marketing teams with data to support pricing, packaging, and pipeline/deal quality
Data as a Product
Support the evolution of Lucra’s client-facing analytics dashboards. Improve clarity, usability, and storytelling across all client-facing data deliverables
Lead the evolution of Lucra’s data offering as a monetizable product, extending beyond dashboards
Distinguish table-stakes analytics from revenue-generating differentiators,
Define and package high-value data assets that customers can purchase as premium add-ons.
Help establish data as an ongoing managed service. Position data-driven upsells that increase ARPU and deepen customer lock-in.
AI & Automation Readiness
Identify practical AI and automation opportunities (forecasting, anomaly detection, workflow automation)
Ensure data cleanliness and structure support AI initiatives
Identify, evaluate, and deploy AI-powered tooling that automates analysis and expands who across the company can work with data.
Design and implement AI-enabled workflows that reduce manual effort
Partner cross-functionally to embed AI analytics tooling into day-to-day workflows across the company