Sr. Data Science Engineer, GTM

AppFolio is a technology leader in the real estate industry, seeking a Senior Data Science Engineer to join their Business Data Platform team. This role focuses on designing and maintaining data pipelines, defining business metrics, and ensuring data quality to support AI and BI initiatives.

Responsibilities:

• Design and Maintain Data Pipelines that ingest data from important business systems to Snowflake via Fivetran. Establish SLAs based on business needs, and design pipelines and processes to meet them
• Define and Deliver Shared Business Metrics by partnering with representatives across the business to align on metric definition and to deliver data mart models and semantic views to serve as the source of truth for tracking metrics
• Lead migration efforts to drive adoption of your new gold standard Data Mart assets across our reporting layer through gaining an understanding of analytics requirements and business processes reliant on other data sources
• Own the evergreen data transformation requirements of Business technologies, and curation of data for broad applicability
• Partner cross-functionally to combine or create add-on services enablement to adoption funnel data models to power objectives for customer targeting and product upsell opportunities
• Activate GTM Datasets created in the Business Data Platform back into Business Systems through reverse ETL Pipelines
• Identify data quality issues and implement semantic data layer standards

Requirements:

• Minimum of 6+ years of work experience in Analytics Engineering, Data Engineering, Data Science, or Data Analytics
• 6+ years of experience supporting analytical data requirements of core internal business applications
• Full Stack Data Science experience: Demonstrated success in bridging the gap between high-level project requirements and complex application data
• Data engineering: expertise in dbt, Snowflake, object-oriented programming, version control, and the technical skills to build and deploy model pipelines to production. Experience creating/maintaining widely adopted production tables
• Data analysis, visualization, and exploration: Exploratory data analysis skills are a critical tool for every full-stack data science engineer, and the results help answer important business questions
• Proficiency in SQL and Python-based (Pandas and/or Spark) approaches for data transformation
• Communication - You have a wealth of experience helping teams make data-driven decisions
• Technical skills – Create and maintain data models, tables, and dashboards needed to manage and scale our Sales and Marketing teams
• Business acumen – understands key challenges facing our business and partners with key stakeholders to find creative ways to apply data analytics to solve them; connects dots between data & business outcomes
• Attention to detail – Proactively checks all work for errors and does not let important details slip when it comes to data and its accuracy
• Cross-Functional Knowledge: Navigates across verticals and functions and understands how each department contributes to our mission. Able to build relationships and quickly establish trust with others to make things happen. Brings teams and people together to accomplish important things
• Efficiency – able to quickly iterate on data generation and refinement. Looks for ways to improve processes to maximize efficiency and remove redundancy