Summary:

　　As a data engineer in Meta's Shops-Ads Advertiser Adoption team you will help eCommerce advertisers maximize ROI by adopting Shops Ads.The adoption team owns the advertiser experience and helps advertisers to try Shops ads by onboarding directly from Ads Manager, shift budget by transitioning BAU Ads to Shops Ads from all major flows and understand performance of onsite conversions across all types of 3P reporting tools.As a highly collaborative organization, our data engineers work cross-functionally with software engineering, data science, and product management to optimize growth, strategy, and experience for our 3 billion plus users, as well as our internal employee community. In this role, you will see a direct correlation between your work, company growth, and user satisfaction. Beyond this, you will work with some of the brightest minds in the industry, and you'll have a unique opportunity to solve some of the most interesting data challenges with efficiency and integrity, at a scale few companies can match.

　　Required Skills:

　　Data Engineer, Shops Ads - Buyer Personalization (TLV) 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 SLA 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 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

　　Minimum Qualifications:

　　Minimum Qualifications:

　　Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

　　4+ years of work experience in data engineering (a minimum of 2+ years with a Ph.D)

　　Experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala, etc.)

　　Preferred Qualifications:

　　Preferred Qualifications:

　　Master's in a STEM field

　　Experience with one or more of the following: data processing automation, data quality, data warehousing, data governance, business intelligence, data visualization, data privacy

　　Experience working with terabyte to petabyte scale data

　　Industry: Internet