Principal Data Analyst

Ethos Watch; Bengaluru; On-site; INR 2,500,000 - 5,500,000; Full time

Job summary

Ethos is a data-driven company, and analytics is at the heart of how we make decisions. We are looking for a Principal Data Analyst who will own and drive the data foundations and self-serve analytics strategy for the company.

This role will be responsible for designing and maintaining the systems, models, and tools that serve as our single source of truth, while empowering stakeholders to independently access and act on insights.

Qualifications

• 8+ years building and scaling data models, pipelines and self-serve analytics systems.
• Expert-level SQL and DBT or equivalent transformation frameworks.
• Hands-on experience with BI/self-serve tools such as Amplitude, Mode, or Looker.
• Strong understanding of event-based data modeling and instrumentation best practices.

Responsibilities

• Design, build and validate foundational data models to serve as the single source of truth for funnels, experiments, and core metrics.
• Build scalable datasets, dashboards, and monitoring systems for self-serve insights.
• Identify and implement AI-driven analytics capabilities to enhance workflows and accessibility of insights.
• Establish monitoring, alerting and documentation to ensure metric reliability.
• End-to-end ownership of analytics solutions from pipelines to executive dashboards.
• Partner with stakeholders to understand top use cases and drive adoption of self-serve tools.
• Define scalable analytics strategy and anticipate future needs.

Skills

SQL

Data modeling

Data pipelines

AI in analytics

Stakeholder communication

Tools

DBT

Amplitude

Mode

Looker

Job description

Job Summary

Ethos is a data-driven company, and analytics is at the heart of how we make decisions. We are looking for a Principal Data Analyst who will own and drive the data foundations and self-serve analytics strategy for the company. This role will be responsible for designing and maintaining the systems, models, and tools that serve as our single source of truth, while empowering stakeholders to independently access and act on insights.

The ideal candidate has a proven track record of building data systems at scale and driving adoption of self-serve analytics. This role requires a rare combination of vision and hands-on execution: you ll set the direction for how data is modeled, monitored, and consumed - and also roll up your sleeves to build, validate, and ship solutions. You ll also explore opportunities to bring AI into analytics workflows, enabling faster, more intuitive self-serve access to insights across the business.

Responsibilities

• Data Foundations: Design, build, and validate event-based foundational data models to serve as the single source of truth for funnels, experiments, and core business metrics.
• Self-Serve Enablement: Build scalable datasets, dashboards, and monitoring systems in tools like Amplitude and Mode to allow teams to self-serve insights.
• AI Integration: Identify and implement AI-driven capabilities to enhance analytics workflows, improve discoverability, and reduce dependency on manual analyst support.
• Reliability Trust: Establish monitoring, alerting, and documentation to ensure accuracy, consistency, and reliability of all core metrics.
• End-to-End Ownership: Scope, design, build, validate, and deploy analytics solutions - from raw data pipelines to executive-facing dashboards.
• Adoption Impact: Partner with stakeholders to understand their top use cases, deliver raw datasets and clean metrics, and ensure broad adoption of self-serve tools.
• Vision Strategy: Anticipate future needs, identify gaps, and define scalable solutions that raise the bar for the analytics function.

Qualifications and Skills

• 8+ years of experience building and scaling data models, pipelines, and self-serve analytics systems.
• Expert-level SQL and strong experience with DBT or equivalent transformation frameworks.
• Hands-on experience with BI/self-serve tools such as Amplitude, Mode, or Looker.
• Deep understanding of event-based data modeling and instrumentation best practices.
• Strong experience building monitoring and alerting for data reliability.
• Ability to translate complex technical concepts into actionable insights for non-technical stakeholders.
• High bar for data quality and accuracy; detail-oriented with strong validation practices.
• Proven track record of driving adoption of self-serve analytics across teams.
• Experience with AI/ML tools to support analytics workflows is a strong plus.

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