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Data Platform Certifications

A route to a Databricks, Snowflake or cloud data engineer credential: choosing the right exam, a guarded trial workspace, hands-on pipelines, timed practice, booking, exam day and where the badge fits a data career.

Free · Mac (Apple silicon) and Windows · v1.0.0 · Other platforms

Then open the Marketplace in the app, search for Data Platform Certifications, and click Install. It goes into your own files, and works offline from then on.

What it installs.

1

Pillar

1

Area

50

Projects

200

Starter tasks

🏅 Tech & Engineering Certifications

Data Platform Certifications

Earning a data credential such as a Databricks, Snowflake or cloud data engineer exam: platform concepts, hands-on practice and how it fits a data career.

  1. Choosing which data platform credential to sit first
  2. Exam guide and current exam facts folder
  3. Skills audit against the exam objectives
  4. Cold baseline practice test
  5. Guarded trial workspace that cannot run up a bill
  6. Lab repository with sample datasets
  7. Dated study calendar to a target exam window
  8. Study materials and course shortlist
  9. Employer sponsorship and voucher request
  10. Twice-weekly study block routine
  11. Weekly lab built and torn down
  12. Wrong-answer review log
  13. Trial credit and lab spend sweep
  14. Monthly timed practice test and score log
  15. Daily flashcards for syntax, limits and defaults
  16. Platform release notes watch
  17. Objective-tagged study notes repository
  18. Quarterly exam version and retirement check
  19. Spark DataFrame fundamentals for Databricks exams
  20. Delta Lake tables, time travel and maintenance
  21. Medallion pipeline lab from raw files to gold tables
  22. Unity Catalog governance and permissions
  23. Snowflake architecture, warehouses and caching
  24. Loading data with stages, COPY, Snowpipe, streams and tasks
  25. Role hierarchy, masking and data sharing in Snowflake
  26. AWS data engineer services map and labs
  27. Microsoft Fabric lakehouse and pipelines for DP-700
  28. Dimensional modelling and SQL performance refresher
  29. Associate or professional level decision
  30. Online proctored or test centre decision
  31. Readiness gate before paying for the exam
  32. Two-week sprint on the weakest domain
  33. Where the credential fits your data career
  34. Booking the exam and the proctor system check
  35. Final fortnight revision plan
  36. Exam day run sheet
  37. Results, digital badge and profile update
  38. Recovery plan after a failed attempt
  39. Analyst moving into analytics engineering
  40. Software engineer moving into data engineering
  41. DBA or ETL developer moving to a cloud lakehouse
  42. Study plan for a working parent
  43. Caribbean and remote candidate exam logistics
  44. Team certification cohort for a data team
  45. Partner consultant certification targets
  46. Data analyst credential on a lakehouse or warehouse
  47. Machine learning credential on a data platform
  48. Professional-level Databricks data engineer preparation
  49. SnowPro advanced data engineer or architect preparation
  50. Capstone portfolio pipeline with documentation

Where it starts.

Each project arrives with its purpose, milestones and first tasks written out. Here is how the first three read.

Choosing which data platform credential to sit first

Data credentials split by platform (Databricks, Snowflake, AWS, Microsoft Fabric, dbt) and by role (engineer, analyst, architect, machine learning), and the wrong first pick costs months on a platform your employer or target employers do not use. Choosing from job adverts and your current stack, rather than from whichever course is on sale, makes the first badge one that shows up in interviews.

First tasks

  • Save twenty job adverts for the data role you want next
  • Tally which platforms and credentials the adverts mention
  • List the data stack your team runs today in one line
  • Write down your chosen first credential and the reason

Exam guide and current exam facts folder

Every data vendor writes its exam from a published guide with domains and objectives, and vendors retire and rename exams often as platforms change: older Azure data engineer exams have been withdrawn and Databricks has renamed several features. A dated folder holding the current guide and the delivery rules keeps every course and practice set checked against the source.

First tasks

  • Download the current exam guide from the vendor's certification site
  • Copy every domain and objective onto one page with a tick column
  • Record the fee, format, validity and retake policy with today's date
  • Note guide topics your chosen course does not mention

Skills audit against the exam objectives

Most candidates already know some of the exam, such as SQL joins or loading files, and none of the rest, such as governance or streaming semantics. Rating yourself honestly against each objective before studying shows where the hours should go and stops you rewatching the parts you could already teach.

First tasks

  • Copy the objective map into a skills matrix
  • Rate each objective for knowledge and hands-on practice
  • Mark the five weakest objectives as study priorities
  • Tag objectives you already meet in your day job

Make it yours.

Install Data Platform Certifications, then tell Aurum the date you're aiming for. It checks whether the plan fits the weeks you actually have.

Free · Mac (Apple silicon) and Windows · v1.0.0 · Other platforms

Blueprints are general information to help you organise your own work. They are not medical, financial, legal or other professional advice. See the Terms.