Databricks data engineering · sources checked October 8, 2026
Choose advanced Databricks training.
Consider Professional instruction for production pipeline design, privacy, performance and controlled deployment.
Exam date matters: the issuer announces a new version for October 9. Its current webpage and guide still disagree on weights; the cutover time zone is unspecified. Rechecked October 8, 2026.
A short request lets Learnerside reply. Research and a private brief are optional; this does not book a course.
Check fit and preparation choices
Best fit
Data engineers designing, diagnosing and deploying production pipelines.
Consider instead
Consider Associate or a targeted module for ingestion, transformation or jobs. Professional is optional.
Before paying
The October 9 exam transition and conflicting current domain weights require date-specific preparation. Course access and final prices also need confirmation.
No-contact next step
Compare a named outline, prepare a private brief or optionally try the fictional case.
Match exam preparation to the date and your background
Databricks Certified Data Engineer Professional is the exact named credential. No separate published alphanumeric exam code was found in the scoped issuer sources. The dual-version October exam guide lists one year of hands-on databricks data engineering recommended. It requires no prior certification or mandatory course; Professional does not require Associate. The certification FAQ separately limits certification to people aged 18 or older. Recommended experience is not a formal employment gate, and open preparation does not prove personal registration eligibility or competence.
Current through October 8, 2026: 59 scored multiple-choice questions, 120 minutes, with English, Japanese, Brazilian Portuguese and Korean listed. New from October 9: 60 scored multiple-choice questions, 120 minutes; the new column lists English only. Either version may include up to ten unscored items, with time allowance already included. Use the version for your scheduled date; the cutover hour and time zone are not specified in the guide.
Current domain-weight conflict: the credential webpage totals 100 percent, while the current column of its linked guide totals 106. Data Sharing and Federation is 5 percent on the page versus 10 in the guide; Data Modeling is 6 versus 7. We have not normalized these numbers or treated either as an agreed preparation allocation. Check the issuer’s latest version before purchasing date-specific exam review.
The guide’s sample-question introduction also uses a date phrase that conflicts with its explicit version table. Use the dated table and confirm the version for your appointment; do not treat the sample section as assured date-specific coverage.
The FAQ does not publish a passing score; a numerical target or claimed pass probability would be unsupported. These are exam facts, not a learner readiness score.
The current ten topic families cover:
Developing Code for Data Processing using Python and SQL
Data Ingestion & Acquisition
Data Transformation, Cleansing, and Quality
Data Sharing and Federation
Monitoring and Alerting
Cost & Performance Optimisation
Ensuring Data Security and Compliance
Data Governance
Debugging and Deploying
Data Modelling
The separate October 9 outline has nine families: Python/SQL code, ingestion, manipulation, monitoring, cost/performance, security/compliance, governance, debugging/deployment and modeling. Its published weights total 100. It is announced future scope as of the October 8 review, not a replacement for the current exam before October 9.
Compare named courses by prerequisites and practice
Advanced Data Engineering with Databricks
Choose when: You already work with Databricks pipelines and need advanced design, privacy, diagnostics and deployment practice.
Four four-hour catalogue modules for experienced SQL/Python, Delta, streaming and DevOps learners. Date-specific exam alignment, selected tuition, personal lab access and feedback remain unverified.
Evidence and entry requirements
Useful evidence: Four four-hour modules cover advanced declarative pipelines, quality and change-data capture, privacy, Spark/Delta performance diagnostics and deployment bundles. The first and fourth modules list notebook-based teaching and Vocareum labs; personal access and reviewed feedback remain unverified. Selected public class listings displayed $1500.00 on October 6, 2026, without a confirmed currency code or final invoice. Taxes, vouchers, seats, recordings and cancellation terms require confirmation. Catalog hours are not a personal study-time guarantee.
Confirm first: The outline expects declarative pipeline knowledge or the earlier pipeline course, Delta Lake, streaming/checkpoints, SQL, Python and Unity Catalog. It also lists intermediate Spark/Python work, Auto Loader, Git, CI/CD and prior DevOps Essentials. These course expectations do not establish exam eligibility. Sixteen catalog hours are not personal preparation time. Entry expectations include declarative pipelines, Delta and streaming/checkpoints, SQL/Python/Unity Catalog, intermediate PySpark, Auto Loader, Git and CI/CD; prior DevOps Essentials is requested. Confirm date-specific exam mapping, learner-operated exercises and feedback.
Choose when: Your immediate gap is foundational pipeline or DevOps work.
Four four-hour catalogue modules; SQL/Python, Spark, Delta and platform knowledge are expected. Selected tuition, personal lab access and feedback remain unverified.
Evidence and entry requirements
Useful evidence: Four four-hour modules cover Lakeflow Connect ingestion, Lakeflow Jobs, Spark Declarative Pipelines and software testing, Git and deployment bundles. The catalog describes notebook-based teaching and Vocareum labs; personal access and reviewed feedback remain unverified. Selected public class listings displayed $1500.00 on October 6, 2026, without a confirmed currency code or final invoice. Taxes, vouchers, seat availability, recordings and cancellation terms require confirmation. Catalog hours are not a personal study-time guarantee.
Confirm first: The modules expect SQL, Python and Databricks platform knowledge, including Spark, Delta Lake, medallion architecture and Unity Catalog. The DevOps module expects proficient platform use, Python with Spark, intermediate SQL, Python and basic Git. Introductory does not mean no starting knowledge. It is not a full Professional preparation promise or a substitute for advanced performance/privacy tasks. Ask which module and exercise addresses your gap before buying the entire course.
The exam guides recommend these named instructor-led courses and also name Academy self-paced modules. Public Academy lesson pages returned a loading shell during this review; that does not establish lesson access. The separate public issuer catalogs above provide readable outlines. Course attendance or a completion badge is not the certification.
The catalog describes notebook-based teaching and Vocareum lab access, with the advanced transition applying to its first and fourth modules. This is provider-described delivery, not verified personal entitlement. Confirm course revision, instructor, language, schedule and time zone, actual lab tasks and access expiry, assessed feedback, recordings, accessibility, voucher inclusion and cancellation terms.
Free Edition can support some practice, with limits
Free Edition documentation describes a no-cost learning environment. The September 29, 2026 limitations specify noncommercial use, serverless-only compute and quotas. Compute may stop after a quota is exceeded; jobs allow up to five concurrent tasks and there is one active pipeline per type. There is no account console, security customization, private networking, SSO/SCIM or guaranteed support/SLA. It therefore does not establish access to every enterprise exercise in either exam or course. No account, identity verification or paid resource was activated here.
The exam guide publishes USD200 plus applicable local taxes per attempt, including both dated Professional versions. This is not the full learning budget. Tuition, compute, practice, retakes, tax and a personal invoice are separate; unknown is not zero.
The two main public course catalogs show selected class rows at $1500.00 as observed October 6, 2026. The display does not establish the currency code, tax, voucher inclusion, cancellation terms, a personal quote or an available seat. Do not silently combine that symbol-only course price with the USD exam base. Class dates shown by a catalog are not a checked registration.
The FAQ requires a 14-day wait after a failed exam. Retakes require the same exam fee; there are no free retakes. Credentials are valid for two years. Recertification requires passing the full current live exam, with its current price and scope; an Academy course badge or Microsoft’s free renewal assessment does not replace it. Check personal expiry, eligibility and appointment before budgeting a renewal.
Connect skills and salary context to actual duties
SQL and Python, ingestion and transformation, data quality, platform/cloud concepts, access/governance and operational problem solving are relevant task associations. Professional emphasizes production design, privacy, performance and controlled deployment. A credential, course or paper exercise does not establish demonstrated proficiency, production authority or a hiring outcome.
U.S. BLS May 2025 occupational data reports median annual pay of USD139,500 for database architects and USD104,620 for database administrators. Use those categories only for matching design/modeling/integration or administration/security/availability duties. A data-engineer title or Databricks credential alone does not establish either mapping. These are U.S. occupation medians, not credential-holder earnings, entry pay, state/local estimates or a certification premium.
Try an original fictional work case
A fictional utility team processes fabricated meter events and a daily correction file. Design a streaming pipeline with late-event and duplicate handling, history tracking, quality quarantine, restricted regional views and a tested multi-environment deployment. Define latency, correctness, privacy and cost checks without using real customer data.
Changed condition: The event rate triples, an event schema changes, and an approved deletion must propagate to derived tables while a deployment is rolled back. Compare performance fixes, deletion evidence and recovery boundaries. Explain which tests and observations must pass before resuming processing.
Review rubric: Justify streaming and storage choices, diagnose a measured bottleneck, preserve data correctness and access boundaries, and define deletion, deployment and rollback evidence. State which enterprise features the learning environment cannot exercise; do not claim production readiness from a paper answer.
This original fictional paper exercise is not an exam question, a readiness score or performed customer work. Use fabricated data and state assumptions; it needs no real account or private data. Later hands-on practice requires an authorized learning environment.
Prepare a private employer training brief
Record the actual pipeline task, baseline SQL/Python/platform knowledge, scheduled exam version if relevant, exact course outline, permitted practice environment, needed review feedback and separate costs. Research and a private brief require no contact details.
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