Company 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.
Job Description
Locations: San Francisco, CA; Sunnyvale, CA; Chicago, IL; New York, NY
At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can both work from home and commute to a LinkedIn office, depending on what’s best for you and when it is important for your team to be together.
LinkedIn is looking for an experienced Data Engineer to support the LinkedIn Marketing Solutions (LMS) execution of complex data development and database efficiency, with a deep focus on improving the data quality, accuracy and timeliness for marketing related products. This role will interact directly with Engineering teams to optimize data operations for product metrics to surface insights at terabyte scale, globally. As our data and business needs increase, we continue to iterate and evolve our processes, best-practice documentation, and deep-dive retrospectives to inform our go/no go decision making. Ultimately to be successful, the individual should feel comfortable advising a team of data professionals, navigating our tech stack, and recommending solutions to complex data problems. Our team is highly collaborative, open and honest, and brings a low-ego, high impact mindset to work!
Responsibilities:
- Design, develop, and manage data pipelines and workflows to enable efficient and accurate data processing using Trino SQL/Spark SQL warehoused in HDFS datasets.
- Effectively performs code designs and reviews/approves test cases.
- Implement data quality checks and audits to maintain high data accuracy and integrity.
- Produces elegant and efficient designs, high performance, and scalable code that allows for easy extension to future needs.
- Collaborate with cross-functional teams, especially data engineering, to understand data requirements and implement robust data solutions.
- Work closely with data domain experts to gather data requirements, translate business needs into technical specifications, and communicate data insights effectively for sales representative workflow efficiency.
- Effectively and actively plays the role of technical advisor and Subject Matter Expert for projects, providing advice on process and design.
- Optimize data storage for performance and scalability, ensuring efficient data Extraction, Transformation and Load (ETL).
- Develop and maintain documentation related to data pipelines, QA, metrics, and data policy as it relates to best practice, compliance and GDPR.
- Stay up to date with industry best practices and emerging trends in data engineering and analytics, including Generative AI as it impacts our data operations.
Qualifications
Basic Qualifications:
- Bachelor's degree in engineering, computer science, data science, or a related technical field.
- 6+ years of experience in a data engineering or analytics engineering role.
- 2+ years of experience using SQL and experience optimizing SQL databases for performance (Trino SQL, or Spark).
- Experience in managing data pipelines (like HDFS), data repository (like GitHub), workflows (like Apache Airflow), and ETL (best practice coding).
- Experience with communicating complex technical concepts to both technical and non-technical individuals.
- Experience working with multiple stakeholders, setting project priorities and delivering on Objectives and Key Results (OKRs).
- Experience automating script changes in Python
Preferred Qualifications
- Masters in engineering, computer science, or related technical field (such as statistics, or data science).
- Excellent analytical skills, designing data workflows and analyzing data for anomalies, or setting data quality thresholds via automated solutions.
- Familiarity with data governance principles
- Program Manager experience
- Demonstrated experience in managing data pipelines in HDFS
- Experience running a scrum team and using Jira.
- Spark SQL
Suggested Skills:
- Data Analysis
- Project Management
- Data Engineering
LinkedIn is committed to fair and equitable compensation practices.
The pay range for this role is $127,000 to $208,000. 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.
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 https://careers.linkedin.com/benefits.
Additional Information
Equal Opportunity Statement
LinkedIn is committed to diversity in its workforce and is 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 an Affirmative Action and Equal Opportunity Employer as described in our equal opportunity statement here: EEO Statement_2020 - Signed.pdf.
Please reference the following information for more information: https://legal.linkedin.com/content/dam/legal/LinkedIn_EEO_Statement_2020.pdf.
Please reference the following information for more information: https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf and
https://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf for more information.
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 accommodations@linkedin.com 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 LinkedIn's 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: https://lnkd.in/paytransparency.
Global 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: https://legal.linkedin.com/candidate-portal.
