Senior Data Analyst

About The Role

We are looking for a technically heavyweight Senior Data Analyst to be the foundational "source of truth" for our Go-To-Market (GTM) and Operations teams. This is a high-autonomy role for an expert executor who can bridge the gap between data and high-stakes business decisions. You will own the data lifecycle — from architecting pipelines and optimizing SQL models to deploying ML forecasting — ensuring our leadership has 100% reliable insights to scale the business.

What Youll Do

• Data Architecture & Modeling: Own the Operational Data Layer that supports core GTM metrics, dashboards, and automation workflows. Design and maintain scalable data models that turn backend data into reliable, clean datasets.
• Technical Ecosystem Ownership: Optimize how GTM data flows between operational database, internal GTM tools and visualization tools to ensure data consistency.
• Advanced Analytics & Insight Delivery
• Develop and deploy ML/AI models for forecasting GTV, optimizing churn, and automating decision-making workflows.
• Design, build, and maintain high-impact dashboards for GTM & Operations teams.
• Perform expert-level ad-hoc analyses using SQL to identify trends, conduct deep-dive research, and deliver objective insights on strategic priorities.
• Data Integrity & Reconciliation: Act as the final gatekeeper for data quality. You will troubleshoot discrepancies, ensuring 100% accuracy.
• Strategic Partnership: Collaborate directly with the Sales, Marketing, Customer Success & Operations teams, identify growth bottlenecks, and automate recurring data needs.
• Project Management & Scoping: Maintain high standards in project delivery, including clear scoping, timeline ownership, and proactive communication with stakeholders.
  

• Experience: 4–6 years in a high-growth start-up environment (Fintech, Payments, or Banking experience is a major plus).
• Modern Data Stack Mastery: Proven experience architecting and maintaining data environments within Snowflake/Clickhouse/Databricks/Other. You understand how to optimize these tools for both cost and performance.
• SQL Mastery: Expert-level SQL (window functions, recursive CTEs, performance tuning). You should be comfortable handling massive datasets and building complex data models.
• Python for Production: Strong Python skills for data manipulation (Pandas/NumPy) and a track record of building automated data workflows and deploying ML models (forecasting, classification, regression).
• Data Engineering Mindset: Experience with transformation and orchestration tools like dbt, Airflow, or Prefect. You know how to build a "gold" data layer from raw, messy sources.
• Analytics & Visualization: Expert in BI tools (Metabase/Tableau/Power BI/Other) with a focus on building high-performance, actionable dashboards.
• First-Principles Thinking: You can take an open-ended business problem, independently scope the technical solution, and drive it to completion.