Pay
Higher than most similar jobs
$231K–$378K against $127K–$190K, the middle half of what similar US postings state.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
Mountain View, CA, United States
Live, first seen by us 17 days agoLinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $231,000 to $378,000. 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.Read the full posting
This role will be based in Mountain View or Bellevue. 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 Data Lake Infrastructure team builds and operates the foundational storage and table-management technologies powering LinkedIn's data platform at massive scale. We own OpenHouse, LinkedIn's open-source control plane for Apache Iceberg tables, along with the broader data lake stack (storage engines, table formats, metadata/catalog services, and compaction/retention systems) that serves thousands of internal teams, petabyte-scale datasets, and mission-critical analytics, ML, and AI workloads. We collaborate closely with open-source communities (Apache Iceberg, Trino, Spark) and partner teams across Data Infrastructure, Analytics, and AI Platform to ensure reliable, cost-efficient, and governable data access company-wide.Read the full posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Own the technical roadmap and architecture for OpenHouse and core data lake services
Lead design and build of large-scale, highly available distributed systems for Iceberg tables
Drive open-source contributions with Apache Iceberg and related projects
Mentor engineers and lead code and design reviews across the team
Lead technical design reviews and write RFCs and design docs
Own the technical roadmap and architecture for OpenHouse and core data lake services
Lead design and implementation of large-scale, highly available distributed systems handling petabyte-scale Iceberg tables.
Drive open-source contributions and engagement with Apache Iceberg and related ecosystem projects.
Provide technical mentorship and code/design review leadership across the team
Lead technical design reviews, write RFCs/design docs, and drive consensus across stakeholders.
10+ years of industry experience in software design, development, and algorithm related solutions.
10+ years of experience in technical leadership: architecture ownership, mentoring, cross-team influence.
8+ years of experience in table formats (Iceberg/Delta/Hudi), data lake/lakehouse architectures, and query engines (Spark, Trino, Presto).
8+ years building large-scale distributed data systems (storage, databases, data lakes, or data infrastructure)
10+ years of experience in systems programming (Java/Scala/Go) and understanding of distributed systems fundamentals (consistency, replication, metadata management.
8+ years of experience with Open-source contribution experience preferred, especially in Apache Iceberg or similar projects.
Experience in architecting, building, and running large-scale distributed systems.
Deep understanding of concurrency, distributed algorithms, and data structures.
Experience with communication and ability to influence cross-functional teams.
Demonstrated ability to align technical decisions with business outcomes and drive customer-centric innovation.
Preferred Qualifications - MS/PhD in Computer Science or related field. - Experience in architecting, building, and running large-scale distributed systems.
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Higher than most similar jobs
$231K–$378K against $127K–$190K, the middle half of what similar US postings state.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
Day 17
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Well past LinkedIn’s usual: its jobs come down by about day 7.
From 13,630 similar postings that came down, and 55 of LinkedIn’s. Coming down is not always a hire.
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- 8+ years building large-scale distributed data systems (storage, databases, data lakes, or data infrastructure) - 10+ years of experience in systems programming (Java/Scala/Go) and understanding of distributed systems fundamentals (consistency, replication, metadata management. - 8+ years of experience with Open-source contribution experience preferred, especially in Apache Iceberg or similar projects.
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 Data Lake Infrastructure team builds and operates the foundational storage and table-management technologies powering LinkedIn's data platform at massive scale. We own OpenHouse, LinkedIn's open-source control plane for Apache Iceberg tables, along with the broader data lake stack (storage engines, table formats, metadata/catalog services, and compaction/retention systems) that serves thousands of internal teams, petabyte-scale datasets, and mission-critical analytics, ML, and AI workloads. We collaborate closely with open-source communities (Apache Iceberg, Trino, Spark) and partner teams across Data Infrastructure, Analytics, and AI Platform to ensure reliable, cost-efficient, and governable data access company-wide. We are seeking a Principal Technical Lead to drive the technical vision and execution for OpenHouse and LinkedIn's data lake technologies. You will set architectural direction, lead complex cross-team initiatives, and mentor engineers building the next generation of table-management and lakehouse infrastructure. This role combines deep hands-on engineering with technical leadership — you'll design for scale, reliability, and openness while representing LinkedIn in the broader open-source data lake ecosystem.
- Own the technical roadmap and architecture for OpenHouse and core data lake services (catalog, table format, compaction, retention, replication, governance). - Lead design and implementation of large-scale, highly available distributed systems handling petabyte-scale Iceberg tables. - Drive open-source contributions and engagement with Apache Iceberg and related ecosystem projects.
- Lead design and implementation of large-scale, highly available distributed systems handling petabyte-scale Iceberg tables. - Drive open-source contributions and engagement with Apache Iceberg and related ecosystem projects. - Partner with Analytics, AI Platform, and Data Infra teams to align on requirements, integration points, and long-term platform strategy.
- 10+ years of experience in technical leadership: architecture ownership, mentoring, cross-team influence. - 8+ years of experience in table formats (Iceberg/Delta/Hudi), data lake/lakehouse architectures, and query engines (Spark, Trino, Presto). - 8+ years building large-scale distributed data systems (storage, databases, data lakes, or data infrastructure)
- 10+ years of experience in systems programming (Java/Scala/Go) and understanding of distributed systems fundamentals (consistency, replication, metadata management. - 8+ years of experience with Open-source contribution experience preferred, especially in Apache Iceberg or similar projects. Preferred Qualifications
- Demonstrated ability to align technical decisions with business outcomes and drive customer-centric innovation. - Production experience operating Iceberg (or similar table format) infrastructure at multi-petabyte, multi-tenant scale. - Open-source contribution experience strongly preferred, especially in Apache Iceberg, Trino, Spark, or related lakehouse/OSS projects, or similar projects.
- Production experience operating Iceberg (or similar table format) infrastructure at multi-petabyte, multi-tenant scale. - Open-source contribution experience strongly preferred, especially in Apache Iceberg, Trino, Spark, or related lakehouse/OSS projects, or similar projects. - Experience with catalog/metadata services, compaction, retention, and data governance.
- Data Infrastructure - Data Lake, Apache Iceberg, Trino, Spark - Deep understanding of concurrency, distributed algorithms, and data structures.
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
This role will be based in Mountain View or Bellevue.
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 Data Lake Infrastructure team builds and operates the foundational storage and table-management technologies powering LinkedIn's data platform at massive scale. We own OpenHouse, LinkedIn's open-source control plane for Apache Iceberg tables, along with the broader data lake stack (storage engines, table formats, metadata/catalog services, and compaction/retention systems) that serves thousands of internal teams, petabyte-scale datasets, and mission-critical analytics, ML, and AI workloads. We collaborate closely with open-source communities (Apache Iceberg, Trino, Spark) and partner teams across Data Infrastructure, Analytics, and AI Platform to ensure reliable, cost-efficient, and governable data access company-wide.
We are seeking a Principal Technical Lead to drive the technical vision and execution for OpenHouse and LinkedIn's data lake technologies. You will set architectural direction, lead complex cross-team initiatives, and mentor engineers building the next generation of table-management and lakehouse infrastructure. This role combines deep hands-on engineering with technical leadership — you'll design for scale, reliability, and openness while representing LinkedIn in the broader open-source data lake ecosystem.
Come join our infrastructure teams and share the knowledge with a broader community while making a real impact within our company.
Core Responsibilities:
Basic Qualifications
Preferred Qualifications
Suggested Skills:
Additional Information:
You will Benefit from our Culture
We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.
LinkedIn is committed to fair and equitable compensation practices.
The pay range for this role is $231,000 to $378,000. 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.
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.
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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.
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Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.
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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 and Compliance Posters for Job Candidates
Please use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants, as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters: https://www.linkedin.com/legal/candidate-portal.
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.
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LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $231,000 to $378,000. 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.
Mountain View, CA, United States
This role will be based in Mountain View or Bellevue. 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 Data Lake Infrastructure team builds and operates the foundational storage and table-management technologies powering LinkedIn's data platform at massive scale. We own OpenHouse, LinkedIn's open-source control plane for Apache Iceberg tables, along with the broader data lake stack (storage engines, table formats, metadata/catalog services, and compaction/retention systems) that serves thousands of internal teams, petabyte-scale datasets, and mission-critical analytics, ML, and AI workloads. We collaborate closely with open-source communities (Apache Iceberg, Trino, Spark) and partner teams across Data Infrastructure, Analytics, and AI Platform to ensure reliable, cost-efficient, and governable data access company-wide.
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.
Global Data Privacy Notice and Compliance Posters for Job Candidates Please use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants, as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters: https://www.linkedin.com/legal/candidate-portal. Company Description