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HomeCompaniesHighspotPrincipal Software Engineer, Data Engineering

Principal Software Engineer, Data Engineering

Highspot · Seattle · Hybrid · Active · $188,696–$258,391 / year · Lever

Job facts

FieldValue
CompanyHighspot
TitlePrincipal Software Engineer, Data Engineering
Normalized title-
Department / teamProduct / Engineering
LocationSeattle, WA, United States
Work modelHybrid / Hybrid
Employment typeFull Time
Salary$188,696–$258,391 / year
Statusactive
ATS providerLever
Posted / first seen2026-06-15 / 2026-06-16
Changed / last seen2026-06-16 / 2026-06-18

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PageWhat it containsOpen
Company jobsActive postings from Highspot.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Lever.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in Seattle.Open
Department jobsActive postings in Product.Open
Work model jobsActive Hybrid postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyHighspot
Source83766521-4617-420e-ba14-7b02b3360a21
ATS providerLever

Description

About Highspot Highspot is pioneering the category that is fundamentally changing the way companies increase sales productivity. On a mission to transform the way millions of people work with sales enablement, Highspot is committed to building breakthrough software with a spark of magic. We believe a great place to work is about more than the work – it’s about what the company stands for, and how it authentically represents its values in the real world. To this end, we have put intentional focus on creating equitable workspaces for each of our employees. Our goal is to create a culture where everyone feels a deep sense of belonging and is empowered to be an agent of change, with the ability to transform themselves, their workplace, and their world. About the Role We are looking for a Principal Data Engineer to join our growing Data Platform team. This is a rare opportunity to define the technical vision for high-scale data products that power customer-facing analytics, intelligent AI agents, and core product capabilities. Highspot's data engineering challenges are uniquely interesting: our platform generates rich, deeply nested document-oriented data from millions of enterprise interactions – content engagement, CRM activity, sales workflows – and our job is to make all of it available, trustworthy, and fast for radically different consumption patterns. Customer-facing analytics dashboards need pre-aggregated, low-latency reads. Scorecards and reports need flexible dimensional models. AI agents need fresh, contextually assembled data with retrieval characteristics that look nothing like traditional BI. You'll own the architecture that serves all three from a unified foundation. As a Principal Data Engineer, you will shape our overarching data architecture direction and fundamentally influence our data strategy. Your impact will extend well beyond your immediate crew – acting as a vital bridge that coordinates directly with upstream software engineering teams (data producers) as well as downstream engineering and AI teams (data consumers) across multiple organizational pillars. You will lead the technical execution of a high-performing engineering crew, balancing deep architectural pipeline design with advanced data modeling, query optimization, and data trust. Base salary range: $188,696 - $258,391 Employees may also be eligible for bonuses and other forms of compensation. The above represents total expected compensation for this role. Actual compensation will depend on various job-related factors, including, but not limited to, location, experience, and job qualifications. Highspot also offers the following employee benefits for this position: -Comprehensive medical, dental, vision, disability, and life benefits -Health Savings Account (HSA) with employer contribution -401(k) Matching with immediate vesting on employer match -Flexible PTO -8 paid holidays and 5 paid days for Annual Holiday Week -Quarterly Recharge Fridays (paid days off for mental health recharge) -18 weeks paid parental leave -Access to Coaches and Therapists through Modern Health -2 volunteer days per year -Commuting benefits #LI-DL1 Equal Opportunity Statement We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of age, ancestry, citizenship, color, ethnicity, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or invisible disability status, political affiliation, veteran status, race, religion, or sexual orientation. Did you read the requirements as a checklist and not tick every box? Don't rule yourself out! If this role resonates with you, hit the ‘apply’ button. What You'll Do Architect the data platform – drive the technical direction for a scalable, reliable data platform built on a medallion architecture that serves customer-facing analytics, reporting, and agentic AI from a unified foundation. Build and optimize ingestion pipelines – design robust CDC, real-time streaming (Kafka, Flink), and batch processing pipelines that transform complex, nested document-oriented operational data into clean analytical models at enterprise scale. Tame schema complexity – build resilient ingestion and transformation layers that gracefully handle deeply nested, continuously evolving document schemas — deciding where to absorb complexity (ingestion, transformation, or query time) and making those tradeoffs explicit and sustainable. Serve AI and analytics consumption patterns – architect data products that support both traditional BI workloads (pre-aggregated dashboards, dimensional models for scorecards and reports) and emerging AI consumption patterns (low-latency retrieval, contextual assembly, freshness-sensitive agent queries). Own data quality, contracts, and observability – establish the data trust infrastructure that makes cross-team data consumption reliable: schema contracts with upstream producers, data quality monitoring, lineage tracking, freshness SLAs, and clear escalation paths when things break. Drive cost-aware architecture – own Snowflake warehouse optimization, compute governance, and cost-efficient pipeline design. Build the practices and visibility so the team makes principled cost/performance tradeoffs rather than discovering them on the invoice. Bridge producers and consumers – collaborate across organizational boundaries to align upstream software engineering teams and downstream analytics and AI teams around unified data strategies, shared contracts, and engineering standards. Lead and grow the team – technically lead and growth-coach a diverse crew of data engineers. Champion best practices across the full spectrum of data engineering disciplines, from low-level pipeline architecture to sophisticated data modeling and analytical query performance. Your Background What will set you apart: Demonstrated depth in building production data platforms that serve multiple consumption patterns – you've gone beyond traditional BI to support real-time product features, AI/ML workloads, or customer-facing analytics from the same data foundation. Deep experience with the impedance mismatch between document-oriented operational stores and analytical systems – you've dealt with nested, schema-evolving source data (MongoDB, DynamoDB, or similar) and have opinions on where flattening and transformation should live. Hands-on experience with data quality and trust at scale – you've built or operated schema registries, data contracts, quality monitoring, or lineage systems in an environment where multiple teams depend on shared data products. Track record of cost-conscious data architecture – you've optimized Snowflake (or comparable) warehouse spend, designed compute governance policies, or re-architected pipelines to materially reduce cost without sacrificing reliability. Strong instinct for the bridge role: you're as comfortable pushing back on an upstream team's schema change as you are negotiating freshness SLAs with a downstream AI consumer. Foundations: 8+ years of professional software engineering experience, with significant time spent on distributed, data-intensive production systems – including substantial depth in data pipeline and platform architecture. Deep hands-on expertise with modern data technologies: Snowflake, Apache Kafka, Apache Flink, and CDC tooling (Debezium or similar). Experience developing and operating cloud data infrastructure at enterprise scale (AWS preferred), including infrastructure-as-code (Terraform) and CI/CD automation. Strong programming skills in Python, Java, and SQL. You write production-grade code, not just scripts. A track record of designing performant data models that support fast, efficient querying for analytical and product-facing use cases. Strong cross-functional communication skills - you work effectively with software engineers, data scientists, AI teams, and business stakeholders across organizational boundaries. Experience mentoring engineers and building collaborative, high-performing teams.

Full job record

Job IDe790b5427535d74cc16889a88d2162e99d4f910e
Org IDe6bcc865-2795-423b-8267-4aed3341992e
Source ID83766521-4617-420e-ba14-7b02b3360a21
Board ID83766521-4617-420e-ba14-7b02b3360a21
Providerlever
Provider Job Keyc49beaf1-a5fe-4883-865a-d8885fbef5df
TitlePrincipal Software Engineer, Data Engineering
Normalized Title
Statusactive
Activeyes
Location TextSeattle
DepartmentProduct
TeamEngineering
Employment TypeFull time
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
RegionWA
CitySeattle
Salary Rawsalary range: $188,696 - $258,391 Employees may also be eligible for bonuses and other forms of compensation
Salary Min188,696
Salary Max258,391
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://jobs.lever.co/highspot/c49beaf1-a5fe-4883-865a-d8885fbef5df
Apply URLhttps://jobs.lever.co/highspot/c49beaf1-a5fe-4883-865a-d8885fbef5df/apply
First Seen At2026-06-16 07:56:51Z
Last Seen At2026-06-18 07:57:02Z
Last Checked At2026-06-18 07:57:02Z
Last Changed At2026-06-16 07:56:51Z
Inactive At
Source Posted At2026-06-15 18:22:09Z
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=lever/board=highspot/date=2026-06-18/2026-06-18T07-57-02-735Z-e504efaf265540c08cf1c47f46e46b319181df3590c3ed25c8a89474c01f1b50.json
Event Fields
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Parsed Structured
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Extensions
{}
Native Structured
{
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    {
      "text": "What You'll Do",
      "content": "<div>\n\n<li>\n<p><strong>Architect the data platform</strong> – drive the technical direction for a scalable, reliable data platform built on a medallion architecture that serves customer-facing analytics, reporting, and agentic AI from a unified foundation.</p>\n</li>\n<li>\n<p><strong>Build and optimize ingestion pipelines</strong> – design robust CDC, real-time streaming (Kafka, Flink), and batch processing pipelines that transform complex, nested document-oriented operational data into clean analytical models at enterprise scale.</p>\n</li>\n<li>\n<p><strong>Tame schema complexity</strong> – build resilient ingestion and transformation layers that gracefully handle deeply nested, continuously evolving document schemas — deciding where to absorb complexity (ingestion, transformation, or query time) and making those tradeoffs explicit and sustainable.</p>\n</li>\n<li>\n<p><strong>Serve AI and analytics consumption patterns</strong> – architect data products that support both traditional BI workloads (pre-aggregated dashboards, dimensional models for scorecards and reports) and emerging AI consumption patterns (low-latency retrieval, contextual assembly, freshness-sensitive agent queries).</p>\n</li>\n<li>\n<p><strong>Own data quality, contracts, and observability</strong> – establish the data trust infrastructure that makes cross-team data consumption reliable: schema contracts with upstream producers, data quality monitoring, lineage tracking, freshness SLAs, and clear escalation paths when things break.</p>\n</li>\n<li>\n<p><strong>Drive cost-aware architecture</strong> – own Snowflake warehouse optimization, compute governance, and cost-efficient pipeline design. Build the practices and visibility so the team makes principled cost/performance tradeoffs rather than discovering them on the invoice.</p>\n</li>\n<li>\n<p><strong>Bridge producers and consumers</strong> – collaborate across organizational boundaries to align upstream software engineering teams and downstream analytics and AI teams around unified data strategies, shared contracts, and engineering standards.</p>\n</li>\n<li>\n<p><strong>Lead and grow the team</strong> – technically lead and growth-coach a diverse crew of data engineers. Champion best practices across the full spectrum of data engineering disciplines, from low-level pipeline architecture to sophisticated data modeling and analytical query performance.</p>\n</li>\n\n</div>"
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      "text": "Your Background",
      "content": "<div style=\"font-size: 11pt; font-family: Calibri, sans-serif; color: #003b6b;\"><span style=\"color: #000000;\"><strong><span style=\"font-size: 11pt;\"><span style=\"font-size: 11pt; font-family: Calibri, sans-serif;\">What will set you apart:</span></span></strong></span></div>\n<ul style=\"margin-top: 0px; margin-bottom: 0px; padding-inline-start: 48px;\">\n<li style=\"font-size: 11pt; font-family: Calibri, sans-serif; color: #000000;\">\n<p style=\"margin-top: 12pt; margin-bottom: 0pt;\"><span style=\"font-size: 11pt; color: #000000;\">Demonstrated depth in building production data platforms that serve multiple consumption patterns – you've gone beyond traditional BI to support real-time product features, AI/ML workloads, or customer-facing analytics from the same data foundation.</span></p>\n</li>\n<li style=\"font-size: 11pt; font-family: Calibri, sans-serif; color: #000000;\">\n<p style=\"margin-top: 0pt; margin-bottom: 0pt;\"><span style=\"font-size: 11pt; color: #000000;\">Deep experience with the impedance mismatch between document-oriented operational stores and analytical systems – you've dealt with nested, schema-evolving source data (MongoDB, DynamoDB, or similar) and have opinions on where flattening and transformation should live.</span></p>\n</li>\n<li style=\"font-size: 11pt; font-family: Calibri, sans-serif; color: #000000;\">\n<p style=\"margin-top: 0pt; margin-bottom: 0pt;\"><span style=\"font-size: 11pt; color: #000000;\">Hands-on experience with data quality and trust at scale – you've built or operated schema registries, data contracts, quality monitoring, or lineage systems in an environment where multiple teams depend on shared data products.</span></p>\n</li>\n<li style=\"font-size: 11pt; font-family: Calibri, sans-serif; color: #000000;\">\n<p style=\"margin-top: 0pt; margin-bottom: 0pt;\"><span style=\"font-size: 11pt; color: #000000;\">Track record of cost-conscious data architecture – you've optimized Snowflake (or comparable) warehouse spend, designed compute governance policies, or re-architected pipelines to materially reduce cost without sacrificing reliability.</span></p>\n</li>\n<li style=\"font-size: 11pt; font-family: Calibri, sans-serif; color: #000000;\">\n<p style=\"margin-top: 0pt; margin-bottom: 12pt;\"><span style=\"font-size: 11pt; color: #000000;\">Strong instinct for the bridge role: you're as comfortable pushing back on an upstream team's schema change as you are negotiating freshness SLAs with a downstream AI consumer.</span></p>\n</li>\n\n<p style=\"margin-top: 12pt; margin-bottom: 12pt;\"><span style=\"color: #000000;\"><strong><span style=\"font-size: 11pt; font-family: Calibri, sans-serif;\">Foundations:</span></strong></span></p>\n<ul style=\"margin-top: 0px; margin-bottom: 0px; padding-inline-start: 48px;\">\n<li style=\"font-size: 11pt; font-family: Calibri, sans-serif; color: #000000;\">\n<p style=\"margin-top: 12pt; margin-bottom: 0pt;\"><span style=\"font-size: 11pt; color: #000000;\">8+ years of professional software engineering experience, with significant time spent on distributed, data-intensive production systems –&nbsp; including substantial depth in data pipeline and platform architecture.</span></p>\n</li>\n<li style=\"font-size: 11pt; font-family: Calibri, sans-serif; color: #000000;\">\n<p style=\"margin-top: 0pt; margin-bottom: 0pt;\"><span style=\"font-size: 11pt; color: #000000;\">Deep hands-on expertise with modern data technologies: Snowflake, Apache Kafka, Apache Flink, and CDC tooling (Debezium or similar).</span></p>\n</li>\n<li style=\"font-size: 11pt; font-family: Calibri, sans-serif; color: #000000;\">\n<p style=\"margin-top: 0pt; margin-bottom: 0pt;\"><span style=\"font-size: 11pt; color: #000000;\">Experience developing and operating cloud data infrastructure at enterprise scale (AWS preferred), including infrastructure-as-code (Terraform) and CI/CD automation.</span></p>\n</li>\n<li style=\"font-size: 11pt; font-family: Calibri, sans-serif; color: #000000;\">\n<p style=\"margin-top: 0pt; margin-bottom: 0pt;\"><span style=\"font-size: 11pt; color: #000000;\">Strong programming skills in Python, Java, and SQL. You write production-grade code, not just scripts.</span></p>\n</li>\n<li style=\"font-size: 11pt; font-family: Calibri, sans-serif; color: #000000;\">\n<p style=\"margin-top: 0pt; margin-bottom: 0pt;\"><span style=\"font-size: 11pt; color: #000000;\">A track record of designing performant data models that support fast, efficient querying for analytical and product-facing use cases.</span></p>\n</li>\n<li style=\"font-size: 11pt; font-family: Calibri, sans-serif; color: #000000;\"><span style=\"font-size: 11pt; color: #000000;\">Strong cross-functional communication skills - you work effectively with software engineers, data scientists, AI teams, and business stakeholders across organizational boundaries.</span></li>\n<li style=\"font-size: 11pt; font-family: Calibri, sans-serif; color: #000000;\">\n<p style=\"margin-top: 0pt; margin-bottom: 12pt;\"><span style=\"font-size: 11pt; color: #000000;\">Experience mentoring engineers and building collaborative, high-performing teams.</span></p>\n</li>\n</ul></ul>"
    }
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  "country": "US",
  "createdAt": 1781547729012,
  "updatedAt": null,
  "categories": {
    "team": "Engineering",
    "location": "Seattle",
    "commitment": "Full time",
    "department": "Product",
    "allLocations": [
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  "salaryRange": null,
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