lakehouse architecture jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-10-29, lakehouse architecture appears in 264 job postings indexed by Skillenai over the past 90 days — Data Engineer has the most postings mentioning lakehouse architecture, with demand share up 14.2% vs the prior 4 weeks.
Last updated · 90d ending 2026-10-29
Which roles want lakehouse architecture?
Upload your resume and Skillenai will show which roles your lakehouse architecture experience fits, which skills you already cover, and what is missing.
Frequently asked questions about lakehouse architecture
+Is lakehouse architecture in demand in 2026?
Yes. lakehouse architecture appears in 264 job postings indexed by Skillenai over the 90 days ending 2026-10-29. Data Engineer accounts for the most postings mentioning lakehouse architecture (31.8% of all postings mentioning lakehouse architecture).
+What jobs require lakehouse architecture?
According to the Skillenai jobs index over the 90 days ending 2026-10-29, among roles with at least 20 postings, the highest shares mentioning lakehouse architecture are Senior Data Engineer (10.3% of that role’s postings mention lakehouse architecture), Data Engineering Director (5.9% of that role’s postings mention lakehouse architecture), Azure Data Engineer (5.4% of that role’s postings mention lakehouse architecture).
+What skills are commonly paired with lakehouse architecture?
Across job postings indexed by Skillenai (90 days ending 2026-10-29), lakehouse architecture most often appears alongside SQL, Python, Databricks, data modeling, ETL.
+Where is lakehouse architecture most in demand?
As of 2026-10-29, the metro areas posting the most jobs requiring lakehouse architecture are Bengaluru, New York City, Pune, Toronto, Hyderabad, according to the Skillenai jobs index.
+How can I keep up with new lakehouse architecture content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning lakehouse architecture alongside the jobs index. You can subscribe to a daily email digest of new lakehouse architecture content from your Skillenai account.
+Which skills come before and after lakehouse architecture?
The skill-flow chart shows skills documented in adjacent positions across observed employer changes. An outgoing skill is documented in the following position but not the preceding one. These are ideas to explore, not proven prerequisites, acquisition dates, or levels of mastery. Each ribbon counts employer moves with that skill pair; one move can contribute several pairs.
Weekly indexed postings requiring lakehouse architecture — last 90 days
Career paths around lakehouse architecture
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before lakehouse architecture
Skills after lakehouse architecture
How to read this chart · view counts
Each side is an independent set of observed employer moves, not the same people followed through three stages. Ribbon widths compare move counts within that side. Internal moves are not included.
The following position documents a skill that the preceding position does not. Skills must be linked to both positions, with clear dates and no overlap. One move can connect several skill pairs. These patterns suggest skills to explore; they do not establish prerequisites, when a skill was learned, or a higher skill level.
Source: Skillenai talent graph, historical career profiles. Historical descriptions and coverage can change. Only the leading published connections are shown.
| Connection | Moves |
|---|---|
| Before: SQL DB | 1 |
| Before: Data Lake ingestion | 1 |
| Before: alerting | 1 |
| Before: Third-party APIs | 1 |
| Before: AWS Glue | 1 |
| Before: CF templates | 1 |
| Before: Apache Airflow | 1 |
| Before: on-premise systems | 1 |
| After: Azure Purview | 1 |
| After: ELK Stack | 1 |
| After: Apache Airflow | 1 |
| After: Spark cluster | 1 |
| After: dbt | 1 |
| After: Spark Streaming | 1 |
| After: Azure Functions | 1 |
| After: Synapse Analytics | 1 |
Roles most likely to require lakehouse architecture
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Senior Data Engineer | 3 | 10.3% |
| Data Engineering Director | 4 | 5.9% |
| Azure Data Engineer | 2 | 5.4% |
| Analytics Engineering Director | 1 | 4.5% |
| Data Architect | 28 | 3.8% |
| Sales Specialist | 3 | 3.5% |
| Data Platform Architect | 1 | 3.1% |
| GenAI Engineer | 1 | 2.9% |
| Lead Data Engineer | 2 | 2.7% |
| Data Product Owner | 1 | 2.6% |
Roles with the most lakehouse architecture postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Data Engineer | 84 | 31.8% |
| Data Architect | 28 | 10.6% |
| Software Engineer | 21 | 8.0% |
| Solutions Architect | 17 | 6.4% |
| Solution Architect | 7 | 2.7% |
| Product Manager | 6 | 2.3% |
| Data Analyst | 4 | 1.5% |
| Data Engineering Director | 4 | 1.5% |
| Data Engineering Manager | 4 | 1.5% |
| Engineering Manager | 4 | 1.5% |
Top companies posting jobs requiring lakehouse architecture
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Databricks | 27 |
| Capital One | 11 |
| InPost | 8 |
| General Motors | 6 |
| PwC | 5 |
| Nigel Frank | 5 |
| Gavelytics | 4 |
| Sggovterp | 3 |
| Mastercard | 3 |
| Tieto | 3 |
Job postings indexed over the past 90 days, grouped by resolved employer. Counts are postings, not hires. Companies without a published page appear without a link.
Top metros hiring for lakehouse architecture
| Name | Postings | Share |
|---|---|---|
| Bengaluru | 6 | 2.3% |
| New York City | 6 | 2.3% |
| Pune | 6 | 2.3% |
| Toronto | 6 | 2.3% |
| Hyderabad | 5 | 1.9% |
| San Francisco | 5 | 1.9% |
| London | 4 | 1.5% |
| Milan | 4 | 1.5% |
| Satakha | 4 | 1.5% |
Skills commonly paired with lakehouse architecture
Explore related pages
How this was computed
Weekly job-count charts omit the incomplete current week (weeks start Monday, UTC). Totals include all postings in the stated window. Counts derive from the Skillenai jobs index over the 90 days ending 2026-10-29. Skills are resolved against the Skillenai canonical taxonomy, so the same entity is counted whether a posting writes 'Python', 'Python 3', or 'python'. Role prevalence divides postings mentioning lakehouse architecture by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s lakehouse architecture postings by all lakehouse architecture postings, including postings without a role. Shares need not sum to 100% for the displayed roles. Pages refresh weekly (or daily for the top-50 most-requested skills). Adjusted posting share: 0.1% to 0.1%. Demand share change is the relative percentage change between these adjusted shares. Each employer-and-ATS group has at least 10 postings in each 90-day window; its earlier posting count supplies the same weight in both windows. The panel includes 2,482 identified employers and covers 71% of earlier and 70% of latest indexed postings. Windows: 2026-06-30 to 2026-09-28 and 2026-07-28 to 2026-10-26 (UTC; end dates excluded). The windows overlap by 62 days. Dates reflect indexing, not the employer’s posting date. This measures posting mix, not total hiring or market-wide demand. Matching excludes entrants and exits; changes in crawl completeness within an employer or ATS can still affect the result.
- source
- Skillenai jobs index, deduplicated daily
- entity_id
- 44babb0b8c45bca6
- data_as_of
- 2026-10-29
- window_days
- 90