Senior Staff Data Engineer
Location: Mountain View, California
Posted: December 17, 2016
Reference ID: 565216480
LinkedIn is a deeply data driven company with data driving not only business decisions but also product features and direction -- data is deeply embedded in the LinkedIn DNA. The company has a diversified business model with revenue coming from Talent Solutions, Marketing Solutions and Premium Subscriptions products.
The Data & Analytics Tools & Applications team is responsible for building and maintaining the state-of-the-art data lake/data warehouse system that makes this data available and accessible to the entire company to make data driven decisions. The team works closely with Analysts, Data scientists, Product Managers, Executives and other key parts of the business across the globe to understand their data requirements and build appropriate data solutions and applications that meet or exceed those needs. Engineers are encouraged to think out of the box and play with latest technologies and explore their limits.
LinkedIn is looking for a Sr. Staff Data Engineer to work with data consumers and data providers across the engineering, analytics and business organizations and create the next generation data warehouse to serve their needs. . The ideal candidate will have strong leadership, a deep understanding of business, technical and evolve a scalable end-to-end data architecture. The candidate should feed on challenges and love to be hands on in big data and data warehouse system.
Provides thought leadership and define common cross-domain data standards and best practices, based data governance and data quality methodologies.
Lead efforts to ensure common data architecture strategies are implemented consistently in projects and initiatives to support proper data management.
Setting standards for regulatory compliance, data policy, DMRC and data retention.
Drive efforts to develop methods and tools to ensure consistent definition and use of data across all of stakeholders.
Contributing to the overall strategy and roadmap for data architecture for company wide data warehouse system and data as a service.
Look for opportunities to leverage the data assets to initiate or support the overall LI business and product strategies.
Building strong relationships with engineering and analytics groups within LI, work with the business analysts/engineering teams to define the technical approaches for solving business problems
Enhance, modify and replace current data architecture and technology to address the scalability, performance and agile development and analytical requirements.
BA/BS Degree in Computer Science or related technical discipline, or 10+ years of related practical experience.
6+ years experience in software design, development, and algorithm related solutions.
10+ years professional experience in a data engineer/architect role, specifically designing and implementing an integrated data platform.
Strong demonstration in creating and deploying best practices and methodologies in data integration, data governance, data quality, data regulation, data policy.
End-to-end data warehouse execution knowledge and leadership in big data ecosystems (Hadoop space)
Experience in Java and/or Python development, efficient SQL.
Experience in data modeling, taxonomy, metadata for large data warehouse in distributed systems.