Analytics Engineer

• Architect and own CodeRabbit's BigQuery warehouse as the canonical analytical layer, building on the existing GCP and Fivetran foundation and taking it to a governed, investor-grade standard.
• Design and ship the dbt project end to end, from raw sources through staging and intermediate models to consumer-facing marts, following modern layering and version-control best practices.
• Set the canonical definitions of ARR, NRR, bookings, and lifecycle in the dbt Semantic Layer so BI, Salesforce, and AI agents all read the same number.
• Build the canonical revenue models behind CodeRabbit's full billing model: seat subscriptions, usage-based add-ons, and per-marketplace settlement across our marketplace channels (AWS, GCP, Vercel, and others).
• Build the identity-resolution spine that resolves a single account and person across product, marketing, billing, and CRM, anchored on stable, system-generated identifiers.
• Partner with Growth Engineering to ship the GTM intelligence layer: PQL and PQA scoring, expansion signals, and the single sales-ready queue that reaches reps through reverse ETL and tools like Clay.
• Make the warehouse a first-class interface for AI agents, exposing the semantic layer and Agents Schema as the governed source agents query, with PQA scoring trained in BigQuery ML and Vertex AI.
• Own data governance, including PII protection and a consent and suppression model that gates downstream activation.
• Establish the data practices, definitions, and documentation the company runs on, and serve as the trusted technical partner to Finance, RevOps, Marketing, and Product.

Staff Analytics Engineer

• Lead and contribute to the implementation and maintenance of end-to-end data pipelines and infrastructure, from ingestion through transformation and analytics.
• Develop, test, and optimize data models and data warehouse architecture with a focus on performance, scalability, and reliability.
• Ensure data quality through validation, monitoring, testing, and strong documentation practices.
• Implement and uphold data governance standards, including data dictionaries, lineage, access controls, and clear ownership of business logic.
• Build and maintain BI dashboards and reporting tools that help teams understand performance and make data-informed decisions.
• Support occasional ad hoc and exploratory data analysis to help answer business questions and identify trends.
• Create and maintain comprehensive documentation for data models, pipelines, reporting logic, and key data definitions.
• Collaborate closely with the Senior Analytics Engineer and cross-functional partners to execute on defined workstreams within an established data framework.
• Assist with ad-hoc projects and tasks as necessary.

• Design, develop, and maintain complex ETL solutions using Informatica PowerCenter and/or IICS to support enterprise data integration and reporting needs
• Build and optimize data pipelines, transformations, and workflows aligned to data warehousing and integration best practices
• Partner with application and business teams to integrate data from Salesforce and other enterprise platforms
• Ensure data quality, reliability, and performance through monitoring, troubleshooting, root‑cause analysis, and optimization of ETL processes
• Contribute to cloud‑based data initiatives and support continuous improvement of data engineering standards, documentation, and delivery practices

Senior ETL Developer

• Develop and maintain ETL processes to support data ingestion, transformation, and integration.
• Work with various file formats (TXT, CSV, XML, JSON, YAML) to ensure seamless data processing.
• Implement and optimize ETL workflows using EasyMorph, Databricks, Azure Data Factory, Talend, and Apache Nifi.
• Write clean, efficient, and maintainable code using Python, C#, or Java.
• Ensure data quality, accuracy, and integrity across ETL pipelines.
• Collaborate with data engineers and analysts to define and refine ETL requirements.
• Troubleshoot and resolve ETL failures, ensuring minimal downtime and impact.
• Follow test-driven development (TDD) methodologies to improve reliability and maintainability.
• Maintain and document ETL processes, providing insights and recommendations for improvements.

Associate ETL Engineer

• Design, build, and maintain high-performance data pipelines and orchestration workflows
• Write clean, modular Python code to transform, parse, clean, and enrich large datasets
• Support stakeholders by developing dashboards and visualizations
• Partner closely with marketing analysts, engineers, and data scientists to define and deliver data needs
• Actively participate in agile ceremonies, code reviews, and planning discussions
• Experiment with and use AI coding tools to boost productivity and code quality

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