Analytics Engineer, Go-To-Market Data

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 to deepen their experience in analytics engineering within a high-impact business environment. You will contribute to foundational data systems used across the organization collaborate directly with cross-functional partners and gain exposure to large-scale data operations and production-grade data management practices. 

The ideal candidate has strong technical fundamentals in SQL Python data modeling and distributed data systems enjoys solving data and operational challenges communicates effectively with technical and business stakeholders and is eager to continuously learn and grow within a collaborative engineering environment. 

Responsibilities 

• Develop and maintain scalable data foundations and solutions including pipelines datasets and analytics capabilities that support the Marketing Strategy & Technology organization. 
• Deliver well-defined components of larger data initiatives end-to-end including development testing deployment monitoring and operational support. 
• Contribute to data product reliability quality and usability through data quality validation observability SLA adherence and continuous improvement efforts. 
• Translate business needs into scalable data solutions by partnering with business and technical stakeholders to gather requirements validate assumptions and propose practical implementation approaches. 
• Apply engineering and governance standards for data modeling documentation testing governance and analytics engineering best practices while identifying opportunities to improve maintainability and efficiency. 
• Support and evolve existing data products by troubleshooting issues resolving defects improving performance and reducing technical debt within assigned areas. 
• Collaborate across teams to deliver solutions through code reviews design discussions knowledge sharing and iterative delivery practices. 
• Communicate progress dependencies and risks clearly to stakeholders and escalate blockers appropriately to support successful execution. 
• Build technical and business domain expertise over time to expand ownership deepen analytics engineering capabilities and increase impact. 

Qualifications :

Basic Qualifications 

• Bachelors 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. 

Preferred Qualifications 

• 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). 
• Strong written and verbal communication; able to explain technical work clearly to non-technical partners. 
• Comfortable asking questions seeking feedback and learning quickly in an ambiguous fast-paced environment. 

Suggested Skills: 

• SQL 
• Pipeline development 
• Data Modeling 
• Data Quality and testing 
• Documentation  
• Stakeholder communications 

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is 112000 to 185000.  

Actual compensation packages are based on several factors that are unique to each candidate including but not limited to skill set depth of experience certifications and specific work location. This may be different in other locations due to differences in the cost of labor.  

The total compensation package for this position may also include annual performance bonus stock benefits and/or other applicable incentive compensation plans. For more information visit  Information :

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No

Employment Type :

Full-time