Position Overview:

In your role as a Business Intelligence (BI) Analyst, you will be responsible for implementing scalable analytics infrastructure from our highest value datasets, converting raw data into canonical models and insights that fuel business decision-making all the way up to the c-suite. In this role, you will have the opportunity to work with numerous cross-functional partners in Engineering, Product, and other key aspects of our General & Administrative (G&A) business to standardize critical metrics and build intuitive self-service products via the modern data stack (Snowflake, dbt, Looker, Hex). As Apollo continues to grow, data will be a critical anchor to influence our strategy and thus, this role will have high visibility, agency, and autonomy to expand qualitative analysis at enterprise scale. You will be reporting to the Head of Business Intelligence within the broader Revenue Operations organization.

Responsibilities

• Build golden, certified data tables (via dbt) to standardize all North Star Metrics (NSMs) for all internal Financial and People-related strategic initiatives and operational reporting
• Build source of truth dashboards (via Looker) for functional departments across our business (i.e. Finance, Accounting, BizOps, Talent, People), allowing internal customers to more intuitively understand the overall health of their business
• Capture + catalog firm-level and department-level key performance indicators and their adjacent data products/lineage to help govern and democratize data discovery and literacy across the company
• Innovate and champion key internal BI & Analytics development workflows and productivity initiatives aimed at optimizing efficiency, reducing cost, and heightening scalability for our overall data ecosystem
• Help drive growth for Apollo by identifying new opportunities that will make the product more intuitive and more enjoyable to use
• Partner with teams across Apollo to help estimate and measure the impact of our changes on growth as well as identify other levers which can drive volume sustainably
• Improve access and visibility to our data by data visualizations - using various BI tools - Be a driving influencer on the use and application of analysis; deliver what’s needed, and show what’s possible
• Conduct qualitative & quantitative analysis of user behavior to uncover issues or opportunities to optimize revenue inflow/outflow and other key acquisition or monetization efforts

Requirements:

• Experience with Looker and dbt is strongly preferred
• Quantitative background (professional and/or academic - Math, Statistics, Economics, or Engineering)
• +3 years of experience with SQL and relational data (preferably in MPP databases such as Snowflake)
• Advanced SQL skills for analysis, standardizing queries, and building data infrastructure involving large-scale relational datasets

Outcomes
BI & Analytics’ General & Administrative (G&A) pod, and inherently this role, will be responsible for:

1. With 2-3 months, building all of the canonical infrastructure (dbt models and Looker explores/dashboards) for the Talent Acquisition (TA) team, enabling the ability to measure key North Star Metrics (NSMs) regarding the end-to-end recruiting operations process, helping uncover inefficiencies and best practices, helping ensure that the TA team can drive 100% attainment of P0 hiring plan and other critical OKRs
2. Within 2-3 months, partner cross-functionally with G&A stakeholders (i.e. Finance) and other directly/indirectly impacted parties (i.e. RevOps & Product leadership) to build new multi-product growth model data marts to help unravel and understand acquisition, retention, and expansion in the context of engagement and revenue for all L1 (Product Lines) and L2 (Use Cases), helping inform overall GTM/Growth/Product roadmaps and customer-facing strategies to drive incremental adoption of our highest-leverage product features
3. Within 1 quarter, help champion the implementation of Apollo’s new HRIS (DarwinBox) and gather requirements, model, and incorporate mission-critical employee metadata into relevant use cases (i.e. reporting hierarchies between GTM reps and their managers, understanding performance by tenure in role, trends by functional domain/department, etc.)
4. Within 1-2 quarters, partner with Finance, Accounting, Business Operations, other business stakeholders, and BI peers to help re-architect and optimize our revenue modeling to conform to the growing complexity of our business. This effort will require untethering from Salesforce as source of truth for financial reporting, and encompass building visibility into revenue line-items that will help us understand more acute drivers of expansion, downgrades, and churn