Software Engineer - Data Engineering (ML Platform)

Posted 7 Days Ago
2 Locations
127K-297K Annually
Entry level
Social Media • Software
We serve the public conversation. We believe real change starts with conversation.
The Role
As a Software Engineer in Data Engineering, you will work on building and maintaining efficient data pipelines, collaborate with team members to design and implement new projects, and ensure data products are accurate and reliable. You'll adapt to various infrastructures and solve large-scale problems while supporting internal teams with data tools and libraries.
Summary Generated by Built In

Are you prepared to join the X team and help build the ultimate real-time information-sharing app, revolutionizing how people connect? At X, we’re on a mission to become the trusted global digital public square, committed to protecting freedom of speech and building the future unlimited interactivity. Our goal is to empower every user to freely create and share ideas, fostering open public discourse without barriers. Join us in shaping this thrilling journey where your contribution will be invaluable to our success!

  

Role: Software Engineer - Data Engineering (ML Platform) - All Levels
Location: Palo Alto
Salary Range: $127,000 to $297,000 USD + Equity

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Who We Are: 

The Data Engineering team plays a pivotal role in our organization. We are responsible for crafting robust and highly efficient data pipelines that serve a wide range of stakeholders, including our end-users and internal teams such as Product, AI, Marketing, Ads, and Sales. Additionally, we develop essential tools and libraries that cater to various use cases across X. Our work extends beyond data-centric solutions, encompassing non-data-related challenges, ultimately maximizing the potential of data for the benefit of our diverse user base.

What you’ll do: As a data engineer at X, you will be able to work with large scale data and make sense out of it. You will need to do the actual work, and also work with team members to design, code, ship new projects and also maintain the pipelines afterwards. You will need to adapt to different toolings, infrastructures, and environments quickly and adjust the solution accordingly. You will need to make sure the data product being offered is accurate, reliable and easy to deal with.

Who You Are: We are looking for dedicated engineers to join us. You should have a strong desire to learn the new stacks and ship impactful projects. You will have exposure to solving large scale problems and comfortable doing incremental quality work while building brand new systems to enable future quality improvements. Capable of interpreting product requirements into engineering implementation plans. Effectively communicate with different groups (AI, product, marketing/sales and engineering). You are good at coding, data pipeline toolings and distributed systems.

Requirements: 

  • Extremely committed 

  • Coding in Scala/Java, Python, Rust

  • Knowledge of Spark/Kafka/Flink/SQL and RMDBs/NoSQL

  • Distributed systems and Data Pipeline building experience

  • Willing to learn and work in a fast paced environment

  • In compliance with federal law, all offers are subject to verification of identity and eligibility to work in the US, and completion of the required employment eligibility verification form.  

Top Skills

Java
Python
Rust
Scala
The Company
HQ: San Francisco, CA
1,500 Employees
Hybrid Workplace
Year Founded: 2006

What We Do

We serve the public conversation. We believe real change starts with conversation. That’s why it matters to us that people have a free and safe space to talk. We put people first. Be you, really. That’s how we build trust. Together we’re creating a culture that’s supportive, respectful, and a pretty cool vibe. Sure, we’re not perfect, we’re people. But we’re open and honest about who we are and what we do.

Why Work With Us

Life’s not about a job, it’s about purpose. We believe real change starts with conversation. Here, your voice matters. Come as you are and together we’ll do what’s right (not what’s easy) to serve the public conversation.

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