Difference between Data Scientist and Data Engineer

What do they do?

Data Engineers

  1. Data Engineers design, build, test, integrate, and optimize data collected from multiple sources.
  2. They use Big Data tools and technologies to construct free-flowing data pipelines that facilitate real-time analytics applications on complex data.
  3. Data Engineers also write complex queries to improve data accessibility.

Data Scientist

  1. Data Scientists are more focused on finding answers to crucial business questions such as optimizing business operations, reducing costs, improving customer experience, etc.
  2. Using the data format offered by Data Engineers, Data Scientists ask relevant questions, find hidden patterns, hypothesis, and then reach fitting conclusions.

Skills Needed

Data Engineers

  1. Programming
  2. Distributed systems
  3. System architecture
  4. Database design and configuration
  5. Interface and sensor configuration

Data Scientist

  1. Programming
  2. Cloud computing
  3. Data wrangling
  4. Database management
  5. Data visualization
  6. Probability & statistics
  7. Multivariate calculus & linear algebra
  8. Machine learning & deep learning

What tools they use

Data Engineers

  1. Python
  2. Java
  3. Scala
  4. Distributed systems
  5. Data pipelines tools (IBM infosphere DataStage, Talend, Pentaho, Apache Kafka, etc.)
  6. Big Data frameworks like Hive, Hadoop, Spark, etc.

Data Scientist

  1. Python
  2. Java
  3. Advanced analytics and BI tools like Tableau Public, Rapidminer, KNIME, QlikView, and Splunk.
  4. ML libraries like Tensorflow, Theano, Pytorch, Apache Spark, DLib, Caffe, and Keras, etc.

What Salaries they get?

Data Engineers

  • According to PayScale, the average salary of Data Engineers in India is: INR 843, 140 LPA, whereas, in the US, it is US$ 92,260.

Data Scientist

  • The average salary of a Data Scientist in India is:
  • INR 813,593 LPA, and in the US, it is US$ 96,089.

How to become one?

Data Engineers

  • Earn a bachelor’s degree and begin working on projects.
  • Fine tune your analytics, computer engineering and big data skills
  • Get your first entry-level engineering job/internship
  • Consider pursuing additional professional engineering or big data certifications.
  • Pursue higher education degrees in computer science, engineering, applied mathematics. Physics, or a related field.

Data Scientist

  • Pursue internship with any Data Science firm
  • Take up data science online courses, and courses that teach Statistics, Probability, and Linear Algebra.
  • Learn about basics of Natural Language Processing, Information Extraction, Computer Vision, Bioinformatics, and Speech Processing etc.
  • Explore Optimization, Information Theory and Decision Theory.
  • Obtain any professional data science certification
  • Try managing databases, analyzing data, or designing the databases

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