1 / 11

Top Skills Every Certified Data Engineer Should Master

Data modeling, ETL pipelines, SQL proficiency, big data tools (Hadoop, Spark), cloud platforms (AWS, Azure), data warehousing, Python/Scala coding, data governance, real-time processing, and strong problem-solving with a focus on scalable, secure infrastructure.

Vamsi26
Download Presentation

Top Skills Every Certified Data Engineer Should Master

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Top Skills Every Certified Data Engineer Should Master www.iabac.org

  2. Programming Proficiency Languages: Python, Java, Scala Automate data collection and transformation Build scalable ETL pipelines Integrate with APIs and platforms Optimize performance and reliability www.iabac.org

  3. Data Warehousing & ETL Design & maintain data warehouses Build ETL workflows to prep data Ensure data quality and integrity Support BI and analytics tools www.iabac.org

  4. Big Data Technologies Tools: Hadoop, Spark, Kafka, Hive, Pig Process massive datasets at scale Enable real-time data streaming Use NoSQL databases for flexible storage www.iabac.org

  5. Data Modeling & Database Design Create relational & dimensional models Use normalization/denormalization Define keys, indexes, relationships Support SQL & NoSQL systems www.iabac.org

  6. SQL Mastery Write and optimize complex queries Transform, aggregate, and clean data Embed SQL into ETL pipelines Enable analytics with views and joins www.iabac.org

  7. Cloud Platforms AWS (S3, Glue, Redshift, EMR) Azure (Data Factory, Synapse) GCP (BigQuery, Dataflow, Cloud Storage) Build scalable, distributed systems www.iabac.org

  8. Data Pipeline Orchestration Tools: Airflow, Luigi, Prefect Manage dependencies and scheduling Automate workflows across platforms Use cloud-native orchestration tools www.iabac.org

  9. DevOps & CI/CD for Data Version control with Git Automate testing & deployment (Jenkins, GitHub Actions) Use IaC tools (Terraform, CloudFormation) Monitor pipelines with observability tools www.iabac.org

  10. Soft Skills & Final Thoughts Translate technical concepts for business teams Collaborate with analysts & PMs Document clearly & present insights Embrace Agile, stay updated, and evolve www.iabac.org

  11. Thank You www.iabac.org

More Related