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Staff Data Engineer - Remote

Posted 4 days ago
Software Development
Full Time
USA

Overview

As a Staff Data Engineer, you will be responsible for maintaining and operating the data platform that caters to machine learning workflows, analytics and powers some of the products offered to Apollo customers.

In Short

  • Develop and maintain scalable data pipelines and build new integrations.
  • Develop and improve Data APIs for machine learning/AI products.
  • Implement automated monitoring and alerting features.
  • Ensure production data quality and availability.
  • Write unit/integration tests and document work.
  • Define data models and populate them in the data warehouse.
  • Collaborate with business units to develop long-term data architecture strategies.

Requirements

  • 8+ years of experience in data platform engineering or software engineering.
  • Experience in data modeling, data warehousing, APIs, and data pipelines.
  • Deep knowledge of databases and data warehousing.
  • Bachelor's degree in a quantitative field.
  • Experience using the Python data stack (preferred).
  • Experience deploying data pipelines in the cloud (preferred).
  • Familiarity with technologies like Airflow, Hadoop, and Spark (preferred).
  • Understanding of streaming technologies (preferred).

Benefits

  • Collaboration across departments.
  • Resources and support for personal growth.
  • Autonomy to own your role and impact.
  • Encouragement of bold ideas and experimentation.
  • Focus on customer revenue potential.
Apollo.io logo

Apollo.io

Apollo.io is a dynamic startup focused on providing a world-class onboarding experience for self-service customers in small to medium-sized businesses (SMBs). The company aims to empower new users to effectively utilize its platform within the first 90 days, ensuring they achieve a return on investment. As a collaborative and innovative organization, Apollo.io values the contributions of its Product Specialist team, which plays a crucial role in teaching customers about the product, creating training materials, and continuously improving the onboarding process through shared learnings and feedback.

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