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Lead analysis across the Base44 user journey, including how people discover Base44, what they create, whether apps get to real usage and value, and how it affects the business
Own the data lifecycle from clarifying the question to data quality and the final story; Challenge the why and how, ai and drive solutions
Set up the analytical backbone of this fast growing product by defining the business questions, establishing a coherent measurement map and reporting logic everyone can use
Identify patterns and anomalies across users, markets, and time, and translate findings into clear business implications
Enable decisions at speed by building trustworthy reporting that supports day-to-day prioritization and leadership readouts

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 world-class 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.
Data Engineer, Product Analytics Responsibilities
Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve
Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
Define and manage Service Level Agreements for all data sets in allocated areas of ownership
Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership
Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
Solve our most challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts
Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts
Influence product and cross-functional teams to identify data opportunities to drive impact
Mentor team members by giving/receiving actionable feedback

As a Data Scientist 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, Oculus). By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a varied set of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.

Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Meta. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.

Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.

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.
Data Scientist, Product Analytics Responsibilities
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions

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 world-class 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.
Data Engineer, Product Analytics Responsibilities
Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
Define and manage Service Level Agreements for all data sets in allocated areas of ownership
Solve challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
Improve logging
Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts
Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts
Influence product and cross-functional teams to identify data opportunities to drive impact

If you are a talented Applied Scientist with strong technical skills, a passion for turning data and research into real-world impact, and the ambition to design, experiment, and ship innovative ML and AI solutions, we would love to talk to you!

In our team, you will:

Develop ML models to detect and disrupt cyberattacks.

Collaborate with security experts to incorporate domain knowledge into ML solutions.

Work with truly large-scale data to create and refine high-quality training datasets.

Deploy ML models into production, monitor their performance, and continuously improve them.

Stay up to date with the latest advancements in ML/AI and apply them to complex cybersecurity challenges.