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AnalyticsEngineer,Go-To-MarketData
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“Analytics Engineer, Go-To-Market Data at LinkedIn. Skills: SQL, Data Modeling, Pipeline Development, Data Quality. Develop and maintain scalable data foundations. Deliver well-defined components of data initiatives”
What You'll Achieve.
Enable the Marketing Strategy & Technology organization.; Deliver reliable, high-quality data products.; Improve the reliability, scalability, and usability of core data assets.; Increase impact.
Industry & Context.
Solving data and operational challenges.
What They're Looking For.
Must Have
Bachelor's degree in Computer Science, Data Science, Information Systems, Statistics, Applied Mathematics, Engineering, Business Analytics, or equivalent practical experience., 2+ years of experience in analytics engineering, data engineering, business intelligence, or a closely related data role., 2+ years of experience writing production SQL to build, transform, or operate datasets., 1+ years of experience with distributed data technologies (e. g. , Trino, Presto, Spark SQL) and a workflow orchestrator (e. g. , Airflow)., Working knowledge of data modeling concepts (e. g. , dimensional modeling, fact/dim tables, slowly changing dimensions) and data quality fundamentals (tests, monitoring, freshness)., Experience working with business stakeholders to gather requirements and deliver data outputs.
Nice to Have
Hands-on experience with Python for data work (transformations, scripting, light tooling)., Familiarity with InDBT or a comparable transformation framework., Exposure to GenAI tools for analytics workflows (e. g. , LLM-assisted SQL, AI-enabled documentation, agent prototypes), curiosity matters more than depth at this level., Familiarity with BI and visualization tools (e. g. , Tableau, Power BI)., Exposure to CRM or go-to-market data (e. g. , Salesforce, Microsoft Dynamics, sales/marketing/advertising data)., written and verbal able to explain technical work clearly to non-technical partners., Comfortable asking questions, seeking feedback, and learning quickly in an ambiguous, fast-paced environment.
What You'll Do.
Develop and maintain scalable data foundations
Deliver well-defined components of data initiatives
Contribute to data product reliability
Translate business needs into scalable data solutions
Apply engineering and governance standards
Support and evolve existing data products
Collaborate across teams to deliver solutions
How You'll Work.
Team & Collaboration
Partner with Analytics Engineering, Sales, Strategy & Operations, Engineering, and Data teams.; Collaborate with business and technical stakeholders.; Collaborate across teams through code reviews, design discussions, knowledge sharing, and iterative delivery practices.
Communication Scope
Communicate progress, dependencies, and risks clearly to stakeholders.; Explain technical work clearly to non-technical partners.
Full Job Description
LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun – where everyone can succeed. Join us to transform the way the world works. This role will be based in Sunnyvale, San Francisco, Chicago, or New York. 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 Analytics Engineer, Marketing Strategy & Technology Data Foundations will support the development and maintenance of scalable data foundations, pipelines, and analytics solutions that enable the Marketing Strategy & Technology organization. You will partner closely with Analytics Engineering, Sales, Strategy & Operations, Engineering, and Data teams to help deliver reliable, high-quality data products that support critical business workflows and decision-making. This is a hands-on analytics engineering role focused on building, improving, and operating foundational data solutions. You will contribute to the development of data pipelines, curated datasets, monitoring frameworks, and data quality processes that improve the reliability, scalability, and usability of core data assets. Working alongside senior analytics engineers, you will operate within established architectural patterns and engineering standards while continuing to grow your technical and business expertise. This role is a strong opportunity for someone looking
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