Full-time Description

About Birdeye

Birdeye is the leading agentic marketing platform for multi-location brands.

Companies like H&R; Block, Aspen Dental, and Caesars Entertainment use Birdeye to manage marketing across thousands of locations — from how they get found, to how they convert, to how they retain customers. Our platform replaces disconnected point tools with AI agents that execute work at the location level — responding to reviews, updating listings, publishing content, and driving conversions.

Backed by Marc Benioff, Jerry Yang, and Accel-KKR, Birdeye was named to G2’s 2026 Best Agentic AI Products list — appearing alongside the world’s leading AI companies. We’re expanding rapidly into enterprise, with growing adoption across large, multi-location brands.

The Opportunity

This is a hybrid role that combines data engineering, analytics, and product strategy.

You'll build scalable datasets, design data pipelines, analyze massive amounts of search performance data, and partner with Product, Engineering, and Growth teams to identify what improves SEO and Answer Engine Optimization (AEO) performance across our platform.

Rather than building customer-facing features, you'll build the intelligence that helps us decide what features to build next.

Your work will directly influence our product roadmap by helping answer questions like:

- What product capabilities have the greatest impact on organic visibility?
- Why are certain customers or industries outperforming others?
- How do search engine and AI search algorithm changes affect our customers?
- Which product investments create measurable improvements in rankings, traffic, and conversions?
- Where are our biggest opportunities to improve customer outcomes

What You'll Do

Build the Data Foundation

- Design, build, and maintain scalable data pipelines using SQL, Python, Snowflake, dbt, and modern data engineering practices
- Integrate and model data from Google Search Console, Google Business Profile, analytics platforms, ranking providers, AI visibility datasets, and internal product systems
- Ensure data quality, reliability, governance, and auditability across analytical datasets
- Develop reusable data models that support experimentation, reporting, and long-term product analytics
- Continuously improve the performance and scalability of our analytical data infrastructure

Discover What Drives Organic Performance

- Analyze billions of data points to identify the factors that influence SEO and AEO performance
- Investigate underperforming customers, industries, and locations to determine root causes
- Measure the impact of product features on rankings, visibility, traffic, engagement, and conversions




- Evaluate search engine and AI search algorithm updates across customer cohorts
- Build statistical analyses and experiments that separate correlation from causation
- Identify patterns and opportunities that inform future product investments

Turn Data into Product Strategy

- Build executive dashboards and self-service reporting using contemporary business intelligence and data visualization platforms
- Develop KPIs and measurement frameworks that quantify product impact
- Present transparent, actionable recommendations to Product, Engineering, Growth, and executive leadership
- Partner with Product Managers to prioritize roadmap investments based on measurable customer outcomes
- Translate complex analytical findings into recommendations that improve customer visibility and product performance

Collaborate Across the Business

- Serve as the primary analytical partner across Data Engineering, Product, Growth, Customer Success, and Engineering
- Help define how Birdeye measures success across SEO, AEO, and AI visibility
- Establish scalable methodologies for evaluating product effectiveness
- Champion a culture of experimentation and data-driven decision making

AI-Driven Analytics

We expect AI to be part of how you work—not just something you build for others.

Successful candidates are comfortable leveraging modern AI tools throughout the analytics lifecycle to:

- Accelerate SQL, Python, and data engineering workflows
- Explore large and complex datasets more efficiently
- Generate hypotheses and rapidly validate findings
- Automate repetitive analysis, documentation, and reporting tasks
- Improve productivity while maintaining high standards for data quality and analytical rigor

You understand where AI adds value, where human judgment is essential, and how to combine both to deliver better insights faster.

What We're Looking For

Technical Skills

- Expert-level SQL with experience analyzing large-scale datasets
- Strong Python programming skills for analytics, automation, and data engineering
- Experience designing and maintaining ELT/ETL pipelines
- Experience working with Snowflake or other modern cloud data warehouses
- Experience with dbt or similar data transformation frameworks
- Experience building executive dashboards and self-service reporting using up-to-date business intelligence platforms
- Robust understanding of data modeling, performance optimization,



and analytical best practices

Analytical Skills

- Exceptional analytical and problem-solving abilities
- Experience working with very large datasets and uncovering meaningful patterns
- Strong statistical reasoning and hypothesis-driven analysis
- Experience designing measurement frameworks and evaluating experiments
- Ability to distinguish correlation from causation and communicate findings with confidence
- Excellent communication skills with the ability to translate technical analysis into business recommendations

Domain Knowledge

Experience in one or more of the following areas is preferred:

- SEO and technical SEO
- Local search and Google Business Profile
- Multi-location business analytics
- Digital marketing analytics
- Answer Engine Optimization (AEO)
- AI search platforms and search visibility
- Product analytics or growth analytics

You don't need to be an SEO expert on day one, but you should be excited to become one and apply data to solve complex search visibility challenges.

Requirements

Qualifications

- Bachelor's degree in Computer Science, Data Analytics, Information Systems, Engineering, Mathematics, Statistics, or a related technical field
- 5+ years of experience in Data Engineering, Analytics, Product Analytics, Growth Analytics, or a related role
- Proven experience building scalable data solutions and analytical models
- Experience partnering closely with Product and Engineering teams to influence business decisions
- Demonstrated ability to work independently on ambiguous, data-intensive problems

What Success Looks Like

Within your first year, you will:

- Build trusted datasets that become the source of truth for SEO, AEO, and AI visibility performance
- Identify the product capabilities that have the greatest impact on customer organic visibility
- Create reporting and measurement frameworks used by Product and executive leadership to guide roadmap decisions
- Develop scalable analyses that proactively identify customer performance opportunities
- Help Birdeye continuously improve customer outcomes through data-driven product innovation

Why Join Birdeye?

- Help shape the future of search as AI transforms how consumers discover businesses.
- Work with massive, real-world datasets spanning hundreds of thousands of businesses and millions of search interactions.
- Influence product strategy with data, not just reports.
- Collaborate with talented Product, Engineering, and Growth teams on high-impact initiatives.
- Use up-to-date data engineering practices and AI-powered workflows to solve complex problems at scale.
- Build systems and insights that directly improve the success of businesses around the world.

📌 Senior Data Engineer / Analyst – Search & AI Visibility (Gurugram)
🏢 Birdeye
📍 Gurugram