Data Engineer, Supply Chain
- Fremont, CA
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.
How would Facebook scale to the next billion users? The Infrastructure Supply Chain group is responsible for the strategic analysis to support and enable the continued growth critical to Facebook's infrastructure organization. We are looking for a Data Engineer to not only build data pipelines but also extend our data tools. As a Data Engineer, you will develop a clear sense of connection with our organization and leadership - as Data Engineering is critical investment to scale analytics capabilities and drive strategy. This is a partnership-heavy role. As a member of Infrastructure Supply Chain Analytics team, you will belong to a centralized Analytics and Data Engineering team who partners closely with teams in Facebook's Infrastructure organization. Through the consulting-nature of our team, you will contribute to a variety of projects and technologies, depending on partner needs. Projects include analytics, ML modeling, tooling, services and more.
- Partner with leadership, engineers, program managers and data analyst to understand data needs.
- Design, build and launch efficient and reliable data pipelines transforming data into useful report ready datasets.
- Communicate at scale, through multiple mediums: Presentations, dashboards, company-wide datasets, bots and more.
- Use your data and analytics experience to 'see what's missing' identifying and address data gaps, build monitor to detect data quality issues and partner to establish a self-serve environment.
- Broad range of partners equates to a broad range of projects and deliverables including ML Models, datasets, measurements, services, tools and process.
- Leverage data and business principles to automate data flow, detect business exceptions, build diagnostic capabilities, improve both business and data knowledge base.
- Build data expertise and own data quality for your areas.
- 5+ years of SQL experience.
- 4+ years of Python development experience.
- 3+ years of experience with workflow management engines (i.e. Airflow, Luigi, Prefect, Dagster, digdag.io, Google Cloud Composer, AWS Step Functions, Azure Data Factory, UC4, Control-M).
- 3+ years experience with Data Modeling.
- Experience analyzing data to discover opportunities and address gaps.
- 5+ years experience in custom ETL design, implementation and maintenance.
- Experience working with cloud or on-prem Big Data/MPP analytics platform (i.e. Netezza, Teradata, AWS Redshift, Google BigQuery, Azure Data Warehouse, or similar).
- Experience with more than one coding language.
- Experience in designing and implementing real-time pipelines.
- Experience with data quality and validation.
- Experience with SQL performance tuning and e2e process optimization.
- Experience with anomaly/outlier detection.
- Experience with notebook-based Data Science workflow.
- Experience querying massive datasets using Spark, Presto, Hive, Impala, etc.
- Experience working with Supply Chain or Data Center Operation team.
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