Data Engineer, Product Analytics

Meta; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Meta is seeking a Data Engineer to shape data-driven experiences across its family of apps. You will collaborate with software engineers, data scientists, and product managers to design and build scalable data solutions for billions of users and hundreds of millions of businesses.

You will guide teams by creating data artifacts, refining systems, and ensuring data security and quality, while influencing product direction with actionable insights.

Qualifications

• Proficiency with SQL, ETL, and data modeling.
• Experience programming in at least one language such as Python, C++, C#, or Scala.
• Demonstrated ability to apply AI tools to optimize workflows and drive measurable impact.

Responsibilities

• Design and build scalable data artifacts (datasets, visualizations) to answer key questions.
• Refine data systems, implement logging and data quality controls.
• Shape product development using data to identify opportunities and drive value.
• Communicate insights clearly to partners and influence decision-making.

Skills

SQL

ETL

Data modeling

Python

C++

C#

Scala

AI tools

Education

Bachelor's degree in Computer Science/Engineering or related field

Master's or Ph.D. in STEM

Job description

As a Data Engineer at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Reality Labs, Threads). Your technical skills and analytical mindset will be utilized designing and building some of the world's most extensive data sets, helping to craft experiences for billions of people and hundreds of millions of businesses worldwide.

In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across Meta to optimize growth, strategy, and user experience for our 3 billion plus users, as well as our internal employee community.

You will be at the forefront of identifying and solving some of the most interesting data challenges at a scale few companies can match. By joining Meta, you will become part of a data engineering community dedicated to skill development and career growth in data engineering and beyond.

Data Engineering

You will guide teams by building optimal data artifacts (including datasets and visualizations) to address key questions. You will refine our systems, design logging solutions, and create scalable data models. Ensuring data security and quality, and with a focus on efficiency, you will suggest architecture and development approaches and data management standards to address complex analytical problems.

Product leadership

You will use data to shape product development, identify new opportunities, and tackle upcoming challenges. You'll ensure our products add value for users and businesses, by prioritizing projects, and driving innovative solutions to respond to challenges or opportunities.

Communication and influence

You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent 7+ years of experience where the primary responsibility involves working with data. This could include roles such as data analyst, data scientist, data engineer, or similar positions 7+ years of experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala or others.) Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Master's or Ph.D degree in a STEM field Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)