Career Spotlight: Data Engineer (VIDEO)

Written by Coursera Staff • Updated on

Ever wondered who builds the pipelines that power data-driven companies? That's the Data Engineer!

[Video thumbnail] Data engineering is easy

This Career Spotlight explores the exciting world of data engineering:

  • What Data Engineers ACTUALLY Do: Discover how they design, build, and maintain the systems that collect, store, and process massive amounts of data.

  • Key Responsibilities: From building data pipelines to ensuring data quality and security, we'll cover the crucial roles data engineers play.

  • Is Data Engineering Right for YOU? Find out if you have the technical skills and passion for data to excel in this high-demand field.

Ready to dive into the world of big data and become a data engineering master? Check out these courses to start your journey! 👇

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professional certificate

DeepLearning.AI Data Engineering

Learn the principles of effective data engineering. Build your skills in the high-demand field of data engineering and learn how you can deliver real business value by applying a core set of principles and strategies for developing data systems.

4.8

(419 ratings)

18,504 already enrolled

Intermediate level

Average time: 3 month(s)

Learn at your own pace

Skills you'll build:

Data Management, Data Pipelines, Query Languages, Data Warehousing, Amazon Web Services, Data Architecture, Data Management Platforms, Data Engineering, DataOps, Extract, Transform, Load, Requirements Analysis, AWS Kinesis, Data Storage, Data Lakes, Data Modeling, Infrastructure as Code (IaC), Data Orchestration, Data transformation, Apache Airflow, Performance Tuning, Data Security, The principles of good data architecture, Data Infrastructure, AWS cloud fundamentals, Translating requirements into tool and technology choices, System Requirements, Data Transformation, Cloud Computing, Thinking like a data engineer, Requirements Gathering, Apache Hadoop, Data Manipulation, Real Time Data, Data Processing, Star Schema, Data Mart, Database Design, Data Access, Apache Spark, Feature Engineering, Applied Machine Learning, Spark and PySpark, Data Integration, CI/CD, Networking on the Cloud, NoSQL, Apache Kafka, Data Quality, Batch and Streaming Ingestion, MySQL, Network Troubleshooting, Terraform, Data orchestration, Database Systems, Amazon CloudWatch, Databases, Graph Theory, File Systems, Data storage fundamentals, Database Management Systems, Data warehouse / data lake / data lakehouse architectures, SQL, Advanced SQL, Amazon S3, Cloud Storage, Streaming queries with Apache Flink

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professional certificate

Meta Database Engineer

Launch your career as a Database Engineer. Build job-ready skills for an in-demand career and earn a credential from Meta. No degree or experience required to get started.

4.6

(2,162 ratings)

67,816 already enrolled

Beginner level

Average time: 6 month(s)

Learn at your own pace

Skills you'll build:

SQL and Python syntax, Algorithms, Databases, database management, Software Testing, Programming Principles, MySQL, Tabular records, Big Data, Statistical Programming, database administration, Python Programming, SQL, Database (DB) Design, Database (DBMS), Django (Web Framework), Data Management, Data Model, Data Warehousing, Extraction, Transformation And Loading (ETL), Project Management, Application development, Computer Programming, Cloud Hosting, Application Programming Interfaces (API), Relational Database, Computer Science, Pseudocode, Data Structure, Communication, Github, Version Control, Linux, Web Development, Bash (Unix Shell)

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