About The Company

A US-headquartered life insurance technology company on a mission to make life insurance simple and accessible. Its platform serves consumers, agents and carriers with instant, online products that replace medical exams with a few health questions. The company is data-driven to its core and is building out its analytics function in Bengaluru.

About The Role

We are hiring a Principal Data Analyst to own and drive the data foundations and self-serve analytics strategy for the whole company. You will design and maintain the systems, models and tools that serve as the single source of truth for funnels, experiments and core business metrics, and you will make it possible for teams across the business to answer their own questions without waiting on an analyst.

This is a single opening reporting to a US-based Senior Director of Analytics (Consumer). The role sits at the bridge between data engineering and product analytics: you set the direction for how data is modelled, monitored and consumed, and you also build, validate and ship. You will partner with product, engineering and business leaders in both India and the US.

What You Will Do

Data foundations: design, build and validate event-based foundational data models that are the single source of truth for funnels, experiments and core business metrics.
Self-serve enablement: build scalable datasets, dashboards and monitoring in tools like Amplitude and Mode so that teams can self-serve insights.
AI integration: identify and ship AI-driven capabilities that make analytics faster, more discoverable and less dependent on manual analyst support.
Reliability and trust: establish monitoring, alerting and documentation so every core metric is accurate, consistent and reliable.
End-to-end ownership: scope, design, build, validate and deploy analytics solutions, from raw data pipelines through executive-facing dashboards.
Adoption and impact: partner with stakeholders to understand their top use cases, deliver clean metrics and datasets, and drive broad adoption of self-serve tools.
Vision and strategy: anticipate future needs, identify gaps and define scalable solutions that raise the bar for the analytics function.
Work day to day with US-based analytics leadership, with some overlap with US hours for key syncs.

What We Are Looking For

Must have

8+ years building and scaling data models, pipelines and self-serve analytics systems; 10+ years ideal.
Both halves of the job: strong data architecture and modelling skills, and strong business and analytics stakeholder skills. You can design the warehouse layer and you can turn a product leader's question into a metric they trust.
Expert-level SQL and hands-on experience with dbt or an equivalent transformation framework.
Hands-on experience with BI and self-serve tools such as Amplitude, Mode or Looker.
Deep understanding of event-based data modelling and instrumentation best practices (event taxonomy, tracking plans, funnel and experiment models).
Strong experience building monitoring and alerting for data reliability.
A proven track record of driving adoption of self-serve analytics across teams, with measurable outcomes.
Ability to translate complex technical concepts into actionable insights for non-technical stakeholders.
A high bar for data quality and accuracy; detail-oriented with strong validation practices.
Background in a scaled consumer, fintech or product company where you owned the data foundations for high-volume product or growth analytics.

Strong plus

Experience applying AI or ML tools to analytics workflows (LLM-assisted querying, semantic layers, automated insight discovery, anomaly detection).
Experience with experimentation platforms and A/B testing data models.
Exposure to insurance, lending or other regulated financial products.
Prior experience working with US-based or distributed teams.

Who This Role Suits

A senior individual contributor who leads through craft and influence rather than headcount. Seasoned Staff or Principal analysts and analytics engineers are the natural fit. Current managers are welcome if they are deliberately moving back to hands-on IC leadership and have kept their technical depth current.

Interview process

Five rounds, all virtual unless agreed otherwise: hiring manager round, technical deep dive, two stakeholder interviews, culture fit

Skills: data modeling,self-serve,data architecture,ai in analytics,dbt,sql,product analytics

Principal Data Analyst (Data Foundations and Self-Serve Analytics)