Data Engineering - IC - F

We’re looking for a highly analytical and business-oriented Data Analytics Engineer to join an innovative team building next-generation AI and GenAI products. This role sits at the intersection of analytics, product development, and data engineering, helping teams make smarter decisions through high-quality data, actionable insights, and scalable analytical solutions. This is not a traditional Data Engineering position focused on infrastructure or platform development. Instead, you’ll own analytical domains end-to-end, transforming complex datasets into insights that drive product improvements across AI-powered customer experiences. What You’ll Do Own Data Domains End-to-End

• Design, develop, and maintain scalable analytical data models.
• Ensure data quality, accuracy, consistency, and reliability across critical datasets.
• Build reusable data products and analytical foundations for product teams.
• Support data governance, stewardship, classification, security, and compliance initiatives.
• Monitor and improve data pipeline health through troubleshooting, optimization, and proactive risk management.

Drive Insights & Product Decisions

• Turn large and complex datasets into actionable business insights.
• Build monitoring frameworks, operational dashboards, and quality reporting solutions.
• Analyze product experiments, user behavior, AI model performance, and evaluation outcomes.
• Perform exploratory analysis to validate new product features before launch.
• Partner closely with Product Managers, Engineers, Data Scientists, and Analytics stakeholders to identify opportunities and drive data-informed decisions.

• 3+ years of experience in Analytics Engineering, Data Analytics, Product Analytics, or other highly analytical data-focused roles.
• Strong business and product mindset with the ability to connect data insights to real-world outcomes.
• Experience owning analytical problems from definition through delivery.
• Proven ability to work independently in ambiguous environments and prioritize based on business impact.
• Experience delivering insights to stakeholders and contributing to production environments.

Technical Skills

• Advanced SQL skills with experience working in large-scale analytical environments.
• Strong Python experience, including data processing and analysis.
• Hands-on experience with PySpark.
• Strong understanding of data modeling and modern data warehouse concepts.
• Experience building scalable, maintainable analytical solutions and transformations.
• Comfortable working with structured, semi-structured, and unstructured data, including AI-generated content and text-based datasets.

Nice to Have

• Experience with dbt, Snowflake, Airflow, Argo, or Streamlit.
• Exposure to AI, machine learning, LLM products, evaluation frameworks, or model performance analysis.
• Experience analyzing experimentation results and product performance metrics.

Personal Attributes

• Strong analytical and critical thinking skills.
• Excellent stakeholder management and communication abilities.
• Curious, proactive, and solution-oriented.
• Comfortable translating technical findings into business recommendations.
• Passionate about using data to solve complex product challenges.

Why This Opportunity?

• Work on some of the most exciting AI and GenAI products in the market.
• Own meaningful analytical domains and influence product strategy.
• Collaborate with multidisciplinary teams including Product, Data Science, Engineering, and AI experts.
• Solve complex business problems using data at scale.
• Gain exposure to cutting-edge LLM and AI evaluation workflows.

Interested in learning more? We’d love to hear from you.