Senior Analytics Engineer

Position Overview: 

As a Senior Analytics Engineer, you will be responsible for implementing a scalable analytics infrastructure to empower all analytical purposes for Apollo, converting raw data into verified, well-defined, and standardized assets to empower business decision-making across all layers of the business. In this role, you will have the opportunity to work with numerous cross-functional partners in Engineering, Product, Data Science, and other key aspects of our business (i.e. GTM, G&A) 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 Manager of Analytics Engineering within the broader Business Intelligence organization.

Responsibilities:

• Core Data Models: Design, develop, and maintain essential data models that will be leveraged across various business functions. Your work will ensure consistency and accuracy in the way data is represented and utilized throughout the company.
• Standards and Best Practices: Define and implement data engineering standards and best practices. Provide guidance and support to other teams to ensure adherence to these standards, promoting high-quality data processes and governance.
• Cross-Functional Collaboration: Partner with all parts of the business to understand their requirements and deliver data solutions that align with their needs while considering scalability. Facilitate effective communication and knowledge sharing across teams.
• Strategic Influence: Play a key role in shaping the future direction of the analytics infrastructure as we scale with Apollo. Provide strategic insights and recommendations to enhance the company’s capabilities and drive impact for business decision-making.

• Develop standardized, transformed, and scalable data assets (via dbt) to enable analytical throughput and understanding across the business. 
• Build self-service analytical mechanisms (via Looker and Hex) to allow business stakeholders to assess and make data-driven decisions in their respective areas of the business. 
• Work cross-functionally across Product, Ops, and Go-to-Market stakeholders to gather requirements, develop project plans, and execute high-impact work. 
• 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. 
• Serve as a subject-matter expert regarding our data, champion data literacy, and raise the analytical capability of all folks at Apollo.

Requirements: 

• Tooling experience
  • Advanced SQL development track record
  • Experience working with the modern data stack (Snowflake, Looker, dbt, Hex are bonuses). 
  • Clearly established track record of modeling, transforming, and interpreting data from source to insight.
  • Proficient in Python: data manipulation (Pandas, NumPy), automation (Airflow), and analytics (Scikit-learn, SQLAlchemy)
  • Data Pipeline Orchestration tooling experience (Airflow, Dagster, etc.) and Data Observability tools (Metaplane, Monte Carlo, Datahub, etc.).
• Sound understanding of the SaaS industry and it’s levers of impact, bonus for PLG company understanding (LTV:CAC, Activation levers, Conversion Rates (self serve vs. sales-led))
• Ability to think objectively, especially when approaching new project, and not be swayed by personal or client bias.
• Great time management skills.
• Excellent written and oral communication skills to summarize insights, design data assets, and provide recommendations to audiences of varying levels of technical sophistication.