Senior Data Engineer
Remote, United States
Applications have closed
Apollo.io
Search, engage, and convert over 275 million contacts at over 73 million companies with Apollo's sales intelligence and engagement platform.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. Apollo.io provides sales and marketing teams with easy access to verified contact data for over 270 million B2B contacts, 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. Apollo.io is growing rapidly, with 900% revenue growth since 2021, and is looking for world-class talent to keep building with us.
Your Role & Mission
As a Senior Data Engineer, you will be responsible for maintaining and operating the data warehouse and connecting in Apollo’s data sources.Daily Adventures and 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.Competencies
• Excellent communication skills to work with engineering, product, and business owners to develop and define key business questions and build data sets that answer those questions. • Self-motivated and self-directed • Inquisitive, able to ask questions and dig deeper • Organized, diligent, and great attention to detail • Acts with the utmost integrity • Genuinely curious and open; loves learning • Critical thinking and proven problem-solving skills requiredSkills & Relevant Experience
Required: • 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) Preferred: • Experience using the Python data stack • Experience deploying and managing data pipelines in the cloud • Experience working with technologies like Airflow, Hadoop and Spark • Understanding of streaming technologies like Kafka, Spark StreamingWhat You’ll Love About Apollo
Besides the great compensation package and culture that thrives in openness and excellence, we invest tremendous effort into developing our remote employees’ careers. The team embraces that we have a sole purpose: to help customers maximize their full revenue potential on the Apollo platform. This mindset opens us up to a lot of creative approaches to making customers successful at scale. You’ll be a significant part of a lean, remote team, empowered to really own your role as a proactive educator. We’re very collaborative at Apollo, so you’ll be able to lean on your teammates, even in adjacent departments, to help you achieve lofty goals. You’ll be supported and encouraged to experiment and take educated risks that lead to big wins. And, you’ll have a whole team remotely by your side to help you do it!
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow Architecture Computer Science Data pipelines Data quality Data warehouse Data Warehousing Engineering ETL Hadoop HubSpot Kafka Mathematics Pipelines Python Spark Statistics Streaming
Perks/benefits: Career development
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