Analytics Engineer, Go-To-Market Data

This role will be based in Sunnyvale San Francisco Chicago Omaha 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 Go-To-Market Data (Staff) will lead and scale global data initiatives for the LinkedIn Marketing Solutions (LMS) business powering data-driven decision-making and business growth at an organizational level. As a senior member of the Data Foundations & Operations team within Global Strategy & Operations you will define the vision strategy and implementation of core data capabilities that shape how we operate sell and innovate globally.

This is a highly visible impact-oriented role for someone who thrives at the intersection of data architecture analytics engineering and business strategy. You will partner closely with senior business leaders Engineering Data Science Business Operations and Finance to design and deliver solutions that improve data integrity scale reliably unlock new insights and directly influence business outcomes.

Responsibilities

• Lead high-impact global data initiatives from concept to scale including solution design technical roadmaps prioritization delivery and adoption across cross-functional teams.

• Architect scalable reliable and business-critical datasets and pipelines that power analytics decision-making and automation across the LMS organization.

• Drive organizational success by proactively identifying pain points and opportunities translating business strategy into data solutions and influencing roadmap priorities.

• Serve as a technical thought leader establishing standards processes and best practices for analytics engineering data quality and operational excellence.

• Own and deliver cross-functional solutions that reduce technical debt improve data accuracy simplify workflows and maximize productivity across teams and tools.

• Define and measure success metrics for large-scale projects delivering outsized business impact (e.g. revenue growth operational efficiency adoption).

• Champion the adoption of data products across lines of business enabling teams to self-serve insights and make smarter decisions faster.

• Foster collaboration and alignment across business engineering and data science partners; ensure shared understanding of goals trade-offs and success criteria.

Mentor and guide junior team members serving as a strategic advisor and sounding board on technical and business problems.

Qualifications :

Basic Qualifications:

• Bachelors degree Computer Science Data Science Information Systems / MIS Statistics / Applied Mathematics Software Engineering / Computer Engineering Business Analytics / Business Information Systems or related practical experience.

• 6 years of experience working with data systems or tools in a business setting (e.g. analytics engineering data management business intelligence data science operations or consulting).

• 4 years of experience using SQL to create manage and optimize large datasets.

• 4 years building scalable data solutions to support business needs

Preferred Qualifications

• 5 years of experience designing and scaling business-critical data infrastructure pipelines tools and systems in production.

• Experience with Trino SQL distributed data systems (e.g. Hadoop Spark) and modern data stack technologies.

• Proficiency with BI tools (e.g. Tableau Power BI) and strong understanding of data modeling best practices.

• Proven ability to drive measurable business outcomes through data architecture analytics engineering and cross-functional collaboration.

• Demonstrated experience leading large-scale projects and managing diverse stakeholders independently.

• Expertise in CRM data (preferably Salesforce or Microsoft Dynamics) and understanding of digital media/advertising data ecosystems.

• Track record of driving organizational adoption of data products and leading process change.

• Strong communication skills with the ability to present complex technical solutions to non-technical audiences and senior leadership.

• Bias toward action; comfortable navigating ambiguity and operating in a fast-paced environment.

Suggested Skills:

• SQL Presto and Spark

• Large-Scale Data Architecture

• Analytics Engineering

• Data Infrastructure Design

• Cross-Functional Leadership

LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $138000 to $225000. Actual compensation packages are based on a wide array of factors unique to each candidate including but not limited to skill set years & depth of experience certifications and specific office location. This may differ in other locations due to cost of labor considerations.

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

Equal Opportunity Statement 

We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race color religion creed gender national origin age disability veteran status marital status pregnancy sex gender expression or identity sexual orientation citizenship or any other legally protected class.

LinkedIn is committed to offering an inclusive and accessible experience for all job seekers including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.

If you need a reasonable accommodation to search for a job opening apply for a position or participate in the interview process connect with us at and describe the specific accommodation requested for a disability-related limitation.

Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:

• Documents in alternate formats or read aloud to you
• Having interviews in an accessible location
• Being accompanied by a service dog
• Having a sign language interpreter present for the interview

A request for an accommodation will be responded to within three business days. However non-disability related requests such as following up on an application will not receive a response.

LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about discussed or disclosed their own pay or the pay of another employee or applicant. However employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information unless the disclosure is (a) in response to a formal complaint or charge (b) in furtherance of an investigation proceeding hearing or action including an investigation conducted by LinkedIn or (c) consistent with LinkedIns legal duty to furnish information.

San Francisco Fair Chance Ordinance

Pursuant to the San Francisco Fair Chance Ordinance LinkedIn will consider for employment qualified applicants with arrest and conviction records.

Pay Transparency Policy Statement

As a federal contractor LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: Data Privacy Notice for Job Candidates

Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: Work :

No

Employment Type :

Full-time