Data Insights - Tech Senior Associate

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. 

The ideal candidate will have strong SQL skills to be able to develop, maintain, and improve data assets and pipelines. The candidate should also have strong analytical skills and be adept at deriving, distilling and articulating actionable business insights from large amounts of data. They will contribute to building and maintaining the data environment, and building and enabling solutions for GTM Operations. This role is ideal for those passionate about creating and enhancing robust data systems supporting LinkedIn’s global operational analytics, with a focus on skills including SQL, Spark, and advanced analytics techniques. Using strong communication skills, the role will effectively collaborate with a variety of people and job functions, accomplishing tasks of high complexity and scope, and can perform professionally in a challenging and extremely fast-paced environment.    

What You’ll Do:      

• Design, build, and maintain tables and pipelines within a large-scale data environment, applying architectural principles and data engineering best practices to ensure scalable and usable foundations 

• Leverage LinkedIn’s unique data to create innovative analyses, including developing/deploying predictive models (e.g., forecasting and classification) 

• Write SQL/Python queries to extract necessary data, analyze the results to generate actionable insights and present the findings 

• Collaborate closely with the sales, marketing, engineering and data teams to provide analysis, reporting and tools that inform key stakeholders. 

• Build cross-functional relationships and partner effectively with other teams to drive project success. 

• Make business recommendations, conveying findings at multiple levels including managers and peers through visual displays of quantitative information.