Analytics Engineer – People Data

LinkedIn • Mountain View, CA

6d • Hybrid

About The Position

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. This role can be based in our Sunnyvale, Mountain View, San Francisco or New York offices. We are looking for an Analytics Engineer with experience working with HR – People data, to manage and maintain our semantic layer and data pipelines, while ensuring data quality, integrity, and accuracy. You will work cross-functionally with engineering, data governance, and business stakeholder teams to advance our data and reporting solutions. You will leverage our data to identify key insights and create operational efficiencies, as well as produce accurate and meaningful analysis to drive business decisions. Your work will directly influence workforce planning, talent strategy, and executive decision-making. To be successful in this role you need to be highly analytical, with a strong intellectual curiosity and be comfortable solving ambiguous challenges. You must be able to prioritize multiple tasks in a fast-paced environment. Your stakeholders will not always know what is possible, so it is important that you ask effective questions to get clarity in addition to managing expectations on what you can deliver. Exceptional attention to detail, strong analytical and development skills, proactive communication skills, and an ability to meet tight deadlines will be critical for success in this role.

Requirements

• BA/BS degree or equivalent degree in Computer Science, Information Technology, Information Systems, or a related field.
• 5+ years of experience as an Analytics Engineer, Data Engineer or Analyst / Consultant with an engineering background.
• 5+ years of database design and semantic layer development.
• 5+ years of experience and advanced proficiency in SQL, including data modeling, transformation, and query optimization.
• 5+ years of experience with data visualization tools (e.g., Power BI, Tableau, etc.).
• 1+ years of experience with Python or scripting languages.

Nice To Haves

• 6+ years of work experience managing stakeholders and engineering teams.
• Familiarity with tools including ALM Toolkit, Tabular Editor, SQL Server Management Studio (SSMS), etc.
• Experience in enterprise integration, primarily focused on HR systems and People Analytics tools (Visier, Workday, SmartRecruiters, etc.), Visier preferred.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and data warehousing solutions (Databricks).
• Experience and understanding of ETL/ELT frameworks, data validation, and reconciliation techniques.
• Experience building and supporting data warehouses specifically for HR and People Analytics domains.
• Design and Systems Thinking
• Problem Solving
• Autonomy, Creativity, and Discretion

Responsibilities

• Contribute to the design of the ETL process, driving clean and actionable requirements, and translate business logic into reusable and governed data assets while working with our Talent Engineering teams.
• Support, maintain, and enhance our existing HR Data Warehouse, ensuring it scales with evolving business needs and systems changes
• Proven track record of developing enterprise-level data programs heavily focused on self-service and multi-persona management.
• Maintain comprehensive technical documentation and data dictionaries for warehouse structures, transformations, and integrations.
• Use SQL to extract, clean, and organize data from multiple HR systems, ensuring structured, accurate, and governed reporting, dashboards, and analytics products.
• Influence and collaborate on the global strategy for People Reporting at the enterprise level and establish scalable solutions to support end users.
• Bring critical thinking & problem-solving skills to a range of challenging problems.
• Stay relevant in technology trends that might be used to resolve complex business problems.
• Advocate for and implement best practices in data engineering, testing, and documentation.

Benefits

• LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $116,000 to $193,000. 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level