Senior Data Engineer

Summary

Join Apollo.io as a Senior Data Engineer and play a crucial role in maintaining and operating our data warehouse, connecting various data sources. You will develop and maintain scalable data pipelines, implement automated monitoring and alerting systems, and ensure data quality. This role requires collaboration with various business units and engineering teams to define data models and long-term data platform architecture. The ideal candidate possesses strong communication skills, is self-motivated, and has 5+ years of experience in data engineering. A bachelor's degree in a quantitative field is required, along with proven experience leveraging AI tools. Apollo offers a collaborative and supportive work environment where your contributions matter.

Requirements

• 5+ years experience in data engineering or in data facing role
• Experience in data modeling, data warehousing, and building ETL pipelines
• Deep knowledge of data warehousing with an ability to collaborate cross-functionally
• Bachelor's degree in a quantitative field (Physical / Computer Science, Engineering or Mathematics / Statistics)
• Proven experience leveraging AI tools by demonstrating fluency in integrating AI-driven solutions into their workflows and a willingness to stay current with emerging AI technologies

Responsibilities

• Develop and maintain scalable data pipelines and build new integrations to support continuing increases in data volume and complexity
• Implement automated monitoring, alerting, self-healing (restartable/graceful failures) features while building the consumption pipelines
• Implement processes and systems to monitor data quality, ensuring production data is always accurate and available
• Write unit/integration tests, contributes to engineering wiki and document work
• Define company data models and write jobs to populate data models in our data warehouse
• Work closely with all business units and engineering teams to develop a strategy for long-term data platform architecture

Preferred Qualifications

• Experience using the Python data stack
• Experience deploying and managing data pipelines in the cloud (preferably AWS or GCP)
• Experience working with technologies like Airflow, Hadoop and Spark
• Understanding of streaming technologies like Kafka, Spark Streaming

Benefits

• We invest deeply in your growth, ensuring you have the resources, support, and autonomy to own your role and make a real impact
• Collaboration is at our core—we’re all for one , meaning you’ll have a team across departments ready to help you succeed
• We encourage bold ideas and courageous action , giving you the freedom to experiment, take smart risks, and drive big wins