Senior Analytics Engineer

Apollo.io is the leading go-to-market solution for revenue teams, trusted by over 500,000 companies and millions of users globally, from rapidly growing startups to some of the world's largest enterprises. Founded in 2015, the company is one of the fastest growing companies in SaaS, raising approximately $250 million to date and valued at $1.6 billion. Apollo.io provides sales and marketing teams with easy access to verified contact data for over 210 million B2B contacts and 35 million companies worldwide, along with tools to engage and convert these contacts in one unified platform.

By helping revenue professionals find the most accurate contact information and automating the outreach process, Apollo.io turns prospects into customers. Apollo raised a series D in 2023 and is backed by top-tier investors, including Sequoia Capital, Bain Capital Ventures, and more, and counts the former President and COO of Hubspot, JD Sherman, among its board members.

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.

• 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.

• 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, Num Py), automation (Airflow), and analytics (Scikit-learn, SQL Alchemy)
  • Data Pipeline Orchestration tooling…