BC Skills Academy

Data Engineering Professional

Build reliable pipelines, warehouses and lakehouses end to end

Key facts

About the Data Engineering Professional certification

The Data Engineering Professional certification validates that you can design and operate production data platforms against real business constraints. You will reason about ETL vs ELT, batch vs streaming, and the modern data stack — and turn those choices into concrete pipeline, storage and modeling decisions. The exam covers data-pipeline design and orchestration (DAGs, Airflow concepts, idempotency, backfills), ingestion patterns (CDC, APIs, files, connectors), distributed processing with MapReduce and Apache Spark (RDDs vs DataFrames, transformations vs actions, shuffles, partitioning, lazy evaluation), dimensional data warehousing (Kimball facts and dimensions, SCD types, OLAP vs OLTP), data lakes and the lakehouse (Parquet/ORC, Delta/Iceberg, schema evolution), file formats and compression, data quality, testing and observability, partitioning and bucketing, cost and performance optimization, and data governance, lineage and DataOps. It is tool-agnostic: the principles transfer across Spark, Snowflake, BigQuery, Databricks, Airflow and dbt. Candidates should already hold the SQL & Data Modeling associate credential or equivalent hands-on experience.

Course outline

The Data Engineering Professional — Study Guide course covers:

  1. Pipelines & Orchestration — ETL vs ELT, batch vs streaming, and orchestrating idempotent, backfillable DAGs. (3 lessons)
  2. Data Ingestion — Files, APIs, connectors and Change Data Capture — getting data in reliably. (3 lessons)
  3. Distributed Processing & Spark — MapReduce, RDDs vs DataFrames, lazy evaluation, shuffles and partitioning. (3 lessons)
  4. Dimensional Data Warehousing — Kimball facts and dimensions, star schemas, SCD types and OLTP vs OLAP. (3 lessons)
  5. Data Lakes & the Lakehouse — Object storage, Parquet/ORC, Delta/Iceberg, schema evolution and the medallion architecture. (3 lessons)
  6. Quality, Governance & DataOps — Data quality testing, observability, lineage, governance and cost/performance tuning. (3 lessons)

Prerequisites

Frequently asked questions

Is the Data Engineering Professional certificate verifiable?
Yes. Every certificate issued by BC Skills Academy carries a unique credential ID that anyone can check on the public verification page.
How is the Data Engineering Professional exam structured?
It is a timed, randomized multiple-choice exam of 70 questions in 100 minutes, graded instantly; you need 75% to pass.
Can I get a refund?
Full refund within 7 days of purchase if you have not started the exam. Once the exam has been started or completed, the purchase is no longer refundable.

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