Offer summary

Qualifications:

5+ years experience in platform engineering, data engineering, or a data-facing role., Bachelor's degree in a quantitative field such as Computer Science, Engineering, or Mathematics/Statistics., Deep knowledge of the data ecosystem and ability to collaborate cross-functionally., Experience with Python data stack and cloud-based data pipeline management is preferred..

Key responsabilities:

Architect and build robust, scalable data pipelines for various use cases.

Develop and maintain high-performance APIs using FastAPI for data services.

Collaborate with software engineers, data scientists, and product teams to translate requirements into engineering solutions.

Monitor data flows and platform services to ensure health, quality, and reliability.

Job description

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 Data Platform Engineer, you will play a key role in designing and building the foundational data infrastructure and APIs that power our analytics, machine learning, and product features. You’ll be responsible for developing scalable data pipelines, managing cloud-native data platforms, and creating high-performance APIs using FastAPI to enable secure, real-time access to data services. This is a hands-on engineering role with opportunities to influence architecture, tooling, and best practices across our data ecosystem.

Daily Adventures and Responsibilities

Architect and build robust, scalable data pipelines (batch and streaming) to support a variety of internal and external use cases
Develop and maintain high-performance APIs using FastAPI to expose data services and automate data workflows
Design and manage cloud-based data infrastructure, optimizing for cost, performance, and reliability
Collaborate closely with software engineers, data scientists, analysts, and product teams to translate requirements into engineering solutions
Monitor and ensure the health, quality, and reliability of data flows and platform services
Implement observability and alerting for data services and APIs (think logs, metrics, dashboards)
Continuously evaluate and integrate new tools and technologies to improve platform capabilities
Contribute to architectural discussions, code reviews, and cross-functional projects
Document your work, champion best practices, and help level up the team through knowledge sharing

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 required

Skills & Relevant Experience

Required:

5+ years experience in platform engineering, data engineering or in a data facing role
Experience in building data applications
Deep knowledge of data eco system 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 Streaming

Why You’ll Love Working at Apollo

At Apollo, we’re driven by a shared mission: to help our customers unlock their full revenue potential. That’s why we take extreme ownership of our work, move with focus and urgency, and learn voraciously to stay ahead.

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.

If you’re looking for a place where your work matters, where you can push boundaries, and where your career can thrive—Apollo is the place for you.

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