Key skills
AirflowPySparkPythonSQLAIMLLLMData EngineeringAnalyticsLookerBIPower BISnowflakedbtFivetranSaaSSalesforceCommunicationSales
About this role
Role Overview
- Architect and build the core Growth Analytics data environment with Snowflake as the central platform
- Design, implement, and maintain scalable data pipelines, integrations, and transformation workflows across internal business, product, operational, sales, marketing, finance, and planning systems
- Build trusted, reusable data models and curated datasets to support internal analytics, reporting, forecasting, growth planning, and Strategy & Operations workflows
- Develop and manage BI environments in Power BI and Looker, including semantic models, governed datasets, dashboard foundations, access patterns, and performance standards
- Build AI-ready data layers to support internal intelligence solutions, including structured datasets, metadata, documentation, business definitions, and governed access patterns
- Establish standards for data quality, testing, observability, lineage, documentation, naming conventions, metric definitions, and production reliability
- Partner with internal stakeholders to translate business questions into scalable data products, reporting layers, and analytics-ready infrastructure
- Create and maintain clear documentation for source systems, pipelines, data models, metric definitions, BI assets, and AI-ready datasets
- Lead technical design discussions, make architecture recommendations, and mentor analytics, BI, and data partners on scalable data practices
- Help move AOS from fragmented reporting and manual data processes toward a reliable, governed, and scalable intelligence layer
Requirements
- 8+ years of experience in data engineering, analytics engineering, or related technical role
- Proven experience building data platforms, analytics environments, or major data infrastructure from scratch or through significant transformation
- Deep hands-on experience with Snowflake
- Strong Scripting, SQL and Python skills
- Experience building production-grade pipelines, integrations, orchestration workflows, and transformation logic
- Experience with modern data ingestion tools such as Fivetran, Airflow + Python, dbt, Pyspark or similar technologies
- Experience building BI environments such as Power BI or Looker
- Strong understanding of data modeling, semantic layers, governed metrics, access control, documentation, lineage, data quality, and observability
- Experience preparing data infrastructure for AI, ML, LLM, advanced analytics, or internal intelligence use cases
- Strong communication skills with technical and non-technical stakeholders
- Experience supporting internal analytics, growth analytics, product Strategy & Operations, GTM analytics, finance analytics, or business operations teams
- Experience integrating data from systems such as Salesforce, Marketo, finance platforms, product usage systems, planning tools, and operational systems
- Experience creating AI-ready data assets, metadata layers, governed knowledge layers, feature-ready datasets, or semantic models
- Experience designing standards for BI development, data documentation, metric governance, and data product delivery
- Experience in B2B SaaS, enterprise software, or complex matrixed organizations
Tech Stack
- Airflow
- PySpark
- Python
- SQL
Benefits
- health and financial benefits
- time away and everyday wellness