Data Engineer, Analytics (Family Ecosystems)

Posted 3 days ago
Main Location
Menlo Park, CA, United States
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Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities - we're just getting started.

Our more experienced data engineers are clearly characterized by in-depth technical experience, subject matter expertise and proven progression in leadership responsibility. If you have an interest in owning important and critical problem areas and influencing by building robust company-wide data foundation and tooling, this is the right role for you. You will get to impact the End-to-End (E2E) suite of big-data tools and products that play a critical part in the day-to-day development lifecycle of Data Engineers, Data Scientists, ML Engineers, Research Scientists & Software Engineers.In this role, you will work closely with Data Infrastructure/Product Software Engineering and Product Management teams to foundationally evolve long-term, architecture-driven, E2E analytics development cycle and the Data Products, Platforms, Tools and Infrastructure stacks that underlie such as – Logging, Streaming, Batch/Compute engines (Presto, Spark), Language/APIs, Semantic Data and Metadata models, ML workflows/models, Consumption workflows (Visualization/Notebooks), Data Discovery and so on. You will define and find solutions to complex and often ambiguous problems as a Subject Matter Expert. You will be leveraging your deep knowledge and experience to collaboratively define technical vision, strategy and architecture in three key areas – Semantic Data and Metadata modeling, Large-scale analytics architecture (covering Logging, ETL and Consumption stacks) and Big Data development lifecycle (coding, testing, deploying, discovery etc.). A few examples of the impact and influence of your work: Consistent E2E Data Model and Definition-driven metrics such as Message Sends across the Family of Apps, Data model and metadata-driven, foundational, company-wide Analyics APIs such as User Retention, Evolving Dataframe APIs, Data Models and company-wide lifecycle development from Logging through Consumption through critical company-wide analytics use cases and Enabling consumption and adhoc exploratory workflows for Data Scientists by helping envision and implement large-scale analytics architecture use cases.

  • Craft and own the optimal data processing architecture and systems for new data and ETL pipelines/analytics applications
  • Build and data (dimensional) model core datasets and analytics applications and make them scalable and fault-tolerant
  • Drive comprehensive Technical Vision on fundamental aspects and evolution of Analytics/Data Infra Foundation/Tooling
  • Define and disseminate technical or product strategy clearly for effective outcomes
  • Articulate strategy within teams, effectively communicate with cross-functional
  • articulate solutions and influence leadership
  • Collaborate and work with different cross-functional partners - Data Infrastructure, Product Software Engineering, Data Engineering and Product Management teams - on use cases sto foundationally evolve long-term, architecture-driven, E2E analytics development cycle
  • Technically influence within the function and cross-functional community
  • Build visualizations to provide insights into the data & metrics
  • Immerse yourself in all aspects of the product, understand the problems, and tie them back to data engineering solutions
  • Drive internal process improvements and automating manual processes
  • Provide ongoing proactive communication and collaboration throughout the organization

  • 4+ years’ experience in the data warehouse space
  • 4+ years’ experience working with either a MapReduce or an MPP system
  • 7+ years’ experience in writing complex SQL, Dataframe APIs and ETL processes
  • 4+ years’ experience with object-oriented programming languages
  • 7+ years’ experience with schema design and dimensional data modeling

  • BS/BA in Technical Field, Computer Science or Mathematics
  • Knowledge in Python or Java or Scala or Pandas
  • Experience analyzing data to identify deliverables, gaps, and inconsistencies
  • Experience mentoring team members in their careers
  • Experience collaborating, defining and communicating complex technical concepts to a broad variety of audiences ariety of audiences
  • Experience scaling analytics architecture and worked with open source big-data stacks (Spark, Koalas etc.)

Facebook is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law.Facebook is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at
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Data Engineer, Analytics (Family Ecosystems)
Facebook, Inc.