Data Engineer - Infrastructure strategy

HomeData Engineer - Infrastructure strategy

Job Title: Data Engineer - Infrastructure strategy
Location: Bellevue, WA/ Menlo Park, CA
Duration: 1 Year

Responsibilities

As a member of Infrastructure Strategy Data Engineering, you will belong to a centralized Data Science/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, Client modeling, tooling, services, and more.
Data Engineer, Infrastructure Strategy Responsibilities Partner with leadership, engineers, program managers and data scientists to understand data needs.
Design, build and launch extremely efficient and reliable data pipelines to move data across a number of platforms including Data Warehouse, online caches and real-time systems.
Communicate, at scale, through multiple mediums: Presentations, dashboards, company-wide datasets, bots and more.
Educate your partners: Use your data and analytics experience to 'see what's missing', identifying and addressing gaps in their existing logging and processes.
Broad range of partners equates to a broad range of projects and deliverables: Client Models, datasets, measurements, services, tools and process.
Leverage data and business principles to solve large scale web, mobile and data infrastructure problems.
Build data expertise and own data quality for your areas.

Minimum Qualifications

Strong SQL skills are a MUST
Data Modeling skills are a MUST and considered a portion of the SQL signals we look for For Coding, should have familiarity with major concepts and a comfort level with at least one language of the candidate's choice Problem Solving is required Partnership is less of a thing here as most of the work will be directed by FTE Data Engineers, however this is a PLUS if the candidate exhibits good soft skills
5+ years of Python development experience.
5+ years of SQL 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 Client 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).

Preferred Qualifications

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