Databricks jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-11-06, Databricks appears in 7,703 job postings indexed by Skillenai over the past 90 days — Data Engineer has the most postings mentioning Databricks, with demand share up 9.1% vs the prior 4 weeks.

Last updated · 90d ending 2026-11-06

Postings · last 90 days
7,703
Demand vs prior month
up 9.1% vs the prior 4 weeks
Top role · 24.0% of skill postings
Top hiring metro
Hyderabad

Which roles want Databricks?

Upload your resume and Skillenai will show which roles your Databricks experience fits, which skills you already cover, and what is missing.

Frequently asked questions about Databricks

+Is Databricks in demand in 2026?

Yes. Databricks appears in 7,703 job postings indexed by Skillenai over the 90 days ending 2026-11-06. Data Engineer accounts for the most postings mentioning Databricks (24.0% of all postings mentioning Databricks).

+What jobs require Databricks?

According to the Skillenai jobs index over the 90 days ending 2026-11-06, among roles with at least 20 postings, the highest shares mentioning Databricks are Senior Data Engineer (42.9% of that role’s postings mention Databricks), Data Platform Architect (41.2% of that role’s postings mention Databricks), Data Consultant (33.3% of that role’s postings mention Databricks).

+What skills are commonly paired with Databricks?

Across job postings indexed by Skillenai (90 days ending 2026-11-06), Databricks most often appears alongside Python, SQL, Snowflake, AWS, CI/CD.

+Where is Databricks most in demand?

As of 2026-11-06, the metro areas posting the most jobs requiring Databricks are Hyderabad, Bengaluru, New York City, Toronto, Pune, according to the Skillenai jobs index.

+How can I keep up with new Databricks content and jobs?

Skillenai indexes news, blog posts, and research papers mentioning Databricks alongside the jobs index. You can subscribe to a daily email digest of new Databricks content from your Skillenai account.

+Which skills come before and after Databricks?

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 Databricks — last 90 days

Salary distribution

Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized

Career paths around Databricks

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before Databricks

Before Databrickspython → Databricks: 200 observed employer moves with this skill pairsql → Databricks: 162 observed employer moves with this skill pairTableau → Databricks: 119 observed employer moves with this skill pairPower BI → Databricks: 118 observed employer moves with this skill pairPySpark → Databricks: 96 observed employer moves with this skill pairsnowflake → Databricks: 89 observed employer moves with this skill pairKafka → Databricks: 81 observed employer moves with this skill pairspark → Databricks: 69 observed employer moves with this skill pairDatabrickspython: 200 movespython200 movessql: 162 movessql162 movesTableau: 119 movesTableau119 movesPower BI: 118 movesPower BI118 movesPySpark: 96 movesPySpark96 movessnowflake: 89 movessnowflake89 movesKafka: 81 movesKafka81 movesspark: 69 movesspark69 moves

Skills after Databricks

After DatabricksDatabricks → python: 91 observed employer moves with this skill pairDatabricks → snowflake: 74 observed employer moves with this skill pairDatabricks → sql: 64 observed employer moves with this skill pairDatabricks → AWS Glue: 60 observed employer moves with this skill pairDatabricks → PySpark: 56 observed employer moves with this skill pairDatabricks → Redshift: 55 observed employer moves with this skill pairDatabricks → Tableau: 50 observed employer moves with this skill pairDatabricks → spark: 49 observed employer moves with this skill pairDatabrickspython: 91 movespython91 movessnowflake: 74 movessnowflake74 movessql: 64 movessql64 movesAWS Glue: 60 movesAWS Glue60 movesPySpark: 56 movesPySpark56 movesRedshift: 55 movesRedshift55 movesTableau: 50 movesTableau50 movesspark: 49 movesspark49 moves
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.

Observed connections and move counts
ConnectionMoves
Before: python200
Before: sql162
Before: Tableau119
Before: Power BI118
Before: PySpark96
Before: snowflake89
Before: Kafka81
Before: spark69
After: python91
After: snowflake74
After: sql64
After: AWS Glue60
After: PySpark56
After: Redshift55
After: Tableau50
After: spark49

Roles most likely to require Databricks

Among roles with at least 20 postings in the same period.

RolePostings mentioning skill% of role postings mentioning skill
Senior Data Engineer1242.9%
Data Platform Architect1441.2%
Data Consultant933.3%
Data Solutions Architect731.8%
Data Engineering Manager7631.8%
Data Engineering Lead1430.4%
Cloud Data Engineer1429.2%
Analytics Engineering Director729.2%
Data Engineer1,84528.9%
Data Engineering Director1828.6%

Roles with the most Databricks postings

RolePostings mentioning skillShare of skill postings
Data Engineer1,84524.0%
Software Engineer5617.3%
Data Scientist5507.1%
Data Analyst3334.3%
Data Architect2132.8%
Solutions Architect1612.1%
Forward Deployed Engineer1512.0%
AI Engineer1431.9%
Analytics Engineer1271.6%
Machine Learning Engineer1011.3%

Top companies posting jobs requiring Databricks

Employers ranked by indexed job postings in the last 90 days.

Top companies posting jobs requiring Databricks
CompanyPostings · 90 days
Mastercard205
Capital One97
General Motors95
Accenture92
Sopra Steria79
Bah79
Databricks77
State Street76
Salesforce68
Guidehouse68

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 Databricks

NamePostingsShare
Hyderabad1802.3%
Bengaluru1752.3%
New York City1532.0%
Toronto1411.8%
Pune1321.7%
San Francisco1241.6%
London1211.6%
Dublin861.1%
Warsaw710.9%

Skills commonly paired with Databricks

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 2026-11-06. 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 Databricks by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s Databricks postings by all Databricks 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: 2.7% to 3.0%. 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 2,471 identified employers and covers 71% of earlier and 70% of latest indexed postings. Windows: 2026-07-07 to 2026-10-05 and 2026-08-04 to 2026-11-02 (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
e8b0d094f07f5855
data_as_of
2026-11-06
window_days
90
Compiled by Jared Rand · Data sourced from the Skillenai labor market index