Spark Streaming jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-10-29, Spark Streaming appears in 170 job postings indexed by Skillenai over the past 90 days — Data Engineer has the most postings mentioning Spark Streaming, with demand share up 11.2% vs the prior 4 weeks.
Last updated · 90d ending 2026-10-29
Which roles want Spark Streaming?
Upload your resume and Skillenai will show which roles your Spark Streaming experience fits, which skills you already cover, and what is missing.
Frequently asked questions about Spark Streaming
+Is Spark Streaming in demand in 2026?
Yes. Spark Streaming appears in 170 job postings indexed by Skillenai over the 90 days ending 2026-10-29. Data Engineer accounts for the most postings mentioning Spark Streaming (37.6% of all postings mentioning Spark Streaming).
+What jobs require Spark Streaming?
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 Spark Streaming are Data Platform Architect (6.2% of that role’s postings mention Spark Streaming), Lead Data Engineer (4.1% of that role’s postings mention Spark Streaming), Data Consultant (3.7% of that role’s postings mention Spark Streaming).
+What skills are commonly paired with Spark Streaming?
Across job postings indexed by Skillenai (90 days ending 2026-10-29), Spark Streaming most often appears alongside Python, Kafka, SQL, Java, Flink.
+Where is Spark Streaming most in demand?
As of 2026-10-29, the metro areas posting the most jobs requiring Spark Streaming are Amsterdam, Paris, San Francisco, Beijing, New York City, according to the Skillenai jobs index.
+How can I keep up with new Spark Streaming content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning Spark Streaming alongside the jobs index. You can subscribe to a daily email digest of new Spark Streaming content from your Skillenai account.
+Which skills come before and after Spark Streaming?
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 Spark Streaming — last 90 days
Career paths around Spark Streaming
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before Spark Streaming
Skills after Spark Streaming
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: python | 55 |
| Before: spark | 49 |
| Before: Kafka | 46 |
| Before: PySpark | 44 |
| Before: sql | 41 |
| Before: Hive | 37 |
| Before: Tableau | 34 |
| Before: snowflake | 30 |
| After: python | 36 |
| After: databricks | 32 |
| After: spark | 31 |
| After: PySpark | 29 |
| After: snowflake | 27 |
| After: sql | 21 |
| After: airflow | 21 |
| After: AWS Glue | 21 |
Roles most likely to require Spark Streaming
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Data Platform Architect | 2 | 6.2% |
| Lead Data Engineer | 3 | 4.1% |
| Data Consultant | 1 | 3.7% |
| Data & AI Engineer | 1 | 3.6% |
| Staff Software Engineer | 3 | 2.5% |
| Big Data Engineer | 1 | 2.3% |
| Data Engineering Lead | 1 | 1.9% |
| Integration Developer | 1 | 1.8% |
| ETL Developer | 1 | 1.7% |
| Data Engineering Manager | 4 | 1.7% |
Roles with the most Spark Streaming postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Data Engineer | 64 | 37.6% |
| Software Engineer | 28 | 16.5% |
| Solutions Architect | 18 | 10.6% |
| Machine Learning Engineer | 5 | 2.9% |
| Data Architect | 4 | 2.4% |
| Data Engineering Manager | 4 | 2.4% |
| Engineering Manager | 4 | 2.4% |
| Data Platform Engineer | 3 | 1.8% |
| Forward Deployed Engineer | 3 | 1.8% |
| Kafka Platform Engineer | 3 | 1.8% |
Top companies posting jobs requiring Spark Streaming
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Databricks | 15 |
| Talan | 9 |
| Grab | 9 |
| Barclays | 6 |
| Adyen | 5 |
| Capital One | 5 |
| Vinted | 5 |
| Harvey | 4 |
| Orb | 4 |
| Wise | 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 Spark Streaming
| Name | Postings | Share |
|---|---|---|
| Amsterdam | 10 | 5.9% |
| Paris | 7 | 4.1% |
| San Francisco | 7 | 4.1% |
| Beijing | 5 | 2.9% |
| New York City | 5 | 2.9% |
| Plano | 5 | 2.9% |
| Pune | 4 | 2.4% |
| Seattle | 4 | 2.4% |
| Boston | 3 | 1.8% |
Skills commonly paired with Spark Streaming
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 Spark Streaming by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s Spark Streaming postings by all Spark Streaming 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 2,481 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
- a46938eed18b6614
- data_as_of
- 2026-10-29
- window_days
- 90