Sr. Analytics Engineer

【 About the role 】

We are looking for a Senior Analytics Engineer to join our centralized data team and take ownership of domain-level data modeling, metric standardization, and dashboard delivery that power both product innovation and business growth.

You will collaborate closely with engineers, product managers, and data scientists — actively participating in product development scrums — and will play a critical role in designing data instrumentation, enabling trustworthy insights, and scaling decision-making infrastructure.

【What You’ll Do 】

• Design and maintain tracking plans across our data ecosystem, including naming conventions, event schemas, and user properties.

• Build and maintain data pipelines in Databricks using Python, Spark, SQL with Delta Live Tables (DLT).

• Define, implement, and document core business metrics (e.g. churn, MRR, engagement, conversions) at the data model layer.

• Own and develop Tableau dashboards, delivering clear and actionable insights to business and product stakeholders.

• Collaborate with Data Scientists to integrate model outputs (e.g. churn scores, segmentation) into production-ready datasets and reporting.

• Support self-service analytics and ensure consistency and clarity in metric definitions.

• Leverage AI tools (e.g. ChatGPT, GitHub Copilot, or internal automation) to enhance productivity and improve modeling workflows.

• Ensure data quality, governance, and documentation across all owned datasets and dashboards.

【 Who you are 】

• 3+ years in an Analytics Engineer, Data Engineer (analytics-focused), or BI Engineer role.

• Hands-on experience of building data pipelines on Databricks or Spark environments with Python.

• Knowledge of ELT process patterns, Dimension modeling, and Medallion architecture.

• Strong SQL and experience building and maintaining gold-level datasets.

• Experience designing and maintaining Tableau dashboards for cross-functional teams.

• Comfortable working directly with engineers on event instrumentation and data validation.

• Familiarity with Mixpanel, Braze, or similar event-based tools (Segment, Amplitude, etc.).

• Able to translate business questions into data products, and ensure consistent metric definitions.

• Interest in leveraging AI tools to optimize data development and analysis workflows.

• Strong problem-solving skills and attention to detail.

• Ability to manage multiple projects simultaneously and prioritize effectively.

• Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.