Data Engineer, Product Analytics
Meta
Data Engineer, Product Analytics
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 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 strong 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.
Locations
- Bellevue, WA, USA
- Menlo Park, CA, USA
- Seattle, WA, USA
- Burlingame, CA, USA
- Washington, DC, USA
- New York, NY, USA
- San Francisco, CA, USA
Salary
Estimated Salary Rangemedium confidence
15,000,000 - 45,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- analytical mindsetintermediate
- designing and building data setsintermediate
- collaborate with teamsintermediate
- design/build scalable data solutionsintermediate
- identifying and solving data challengesintermediate
- building optimal data artifactsintermediate
- building datasetsintermediate
- building visualizationsintermediate
- refine systemsintermediate
- design logging solutionsintermediate
- create scalable data modelsintermediate
- ensuring data securityintermediate
- ensuring data qualityintermediate
- suggest architectureintermediate
- suggest development approachesintermediate
- data management standardsintermediate
- address complex analytical problemsintermediate
- use data to shape product developmentintermediate
- identify new opportunitiesintermediate
- tackle challengesintermediate
- prioritizing projectsintermediate
- driving innovative solutionsintermediate
- communicationintermediate
- influenceintermediate
- tell data-driven storiesintermediate
- convince partnersintermediate
- build credibilityintermediate
- structureintermediate
- clarityintermediate
Required Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 2+ 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 2+ years of experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala or others.) Master's or Ph.D degree in a STEM field (experience, 2 years)
Responsibilities
- Manage and execute data warehouse plans for a product or a group of products to solve well-scoped problems Identify the data needed for a business problem and implement logging required to ensure availability of 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 Build data expertise and leverage data controls to ensure privacy, security, compliance, data quality, and operations for allocated areas of ownership Design, build and launch new data models and visualizations in production, leveraging common development toolkits Independently design, build and launch new data extraction, transformation and loading processes in production, mentoring others around efficient queries Support existing processes running in production and implement optimized solutions with limited guidance Define and manage Service Level Agreements for data sets in allocated areas of ownership
Tags & Categories
Data Engineer, Product Analytics
Meta
Data Engineer, Product Analytics
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 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 strong 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.
Locations
- Bellevue, WA, USA
- Menlo Park, CA, USA
- Seattle, WA, USA
- Burlingame, CA, USA
- Washington, DC, USA
- New York, NY, USA
- San Francisco, CA, USA
Salary
Estimated Salary Rangemedium confidence
15,000,000 - 45,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- analytical mindsetintermediate
- designing and building data setsintermediate
- collaborate with teamsintermediate
- design/build scalable data solutionsintermediate
- identifying and solving data challengesintermediate
- building optimal data artifactsintermediate
- building datasetsintermediate
- building visualizationsintermediate
- refine systemsintermediate
- design logging solutionsintermediate
- create scalable data modelsintermediate
- ensuring data securityintermediate
- ensuring data qualityintermediate
- suggest architectureintermediate
- suggest development approachesintermediate
- data management standardsintermediate
- address complex analytical problemsintermediate
- use data to shape product developmentintermediate
- identify new opportunitiesintermediate
- tackle challengesintermediate
- prioritizing projectsintermediate
- driving innovative solutionsintermediate
- communicationintermediate
- influenceintermediate
- tell data-driven storiesintermediate
- convince partnersintermediate
- build credibilityintermediate
- structureintermediate
- clarityintermediate
Required Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 2+ 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 2+ years of experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala or others.) Master's or Ph.D degree in a STEM field (experience, 2 years)
Responsibilities
- Manage and execute data warehouse plans for a product or a group of products to solve well-scoped problems Identify the data needed for a business problem and implement logging required to ensure availability of 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 Build data expertise and leverage data controls to ensure privacy, security, compliance, data quality, and operations for allocated areas of ownership Design, build and launch new data models and visualizations in production, leveraging common development toolkits Independently design, build and launch new data extraction, transformation and loading processes in production, mentoring others around efficient queries Support existing processes running in production and implement optimized solutions with limited guidance Define and manage Service Level Agreements for data sets in allocated areas of ownership
Tags & Categories