In a data centered world, we find a lot of job opportunities as a Data Scientist or Data Engineer for most data-driven organizations.
Both career paths are data-driven, analytical and problem solvers. Data scientist, Data engineer, Data analyst and Business analysts are part of data analytics team and compliment each other based on their job responsibilities.
I will explain and list skills required for both positions in regards to Data Scientist and Data Engineer positions.
DATA SCIENTIST
Data Scientists are analytical problem solvers for complex data problems by analyzing structured and unstructured data to derive meaningful insights.
Data Scientist’s cleanse existing raw data and build models to predict future data to help influence business decisions. Their job varies from descriptive analytics to predictive analytics. Visualization of data is a key part of a Data Scientist job.
To become a Data Scientist, you need to have these skills:
- Analytical mindset
- SQL
- Data mining
- Statistical Modelling
- MS or PHD degree in Computer Science/technical major
- Great Communication skill
- Data Wrangling
- Ability to Visualize data (MS Excel, Power BI, Tableau)
- Programming skills (Python, R)
- Business knowledge
- Machine Learning
Data Engineer
Data Engineers basically design, integrate, manage and implement solutions by setting up data platform technologies and application services to manage data flow from multiple sources to meet business requirements. They get, ingest, transform, validate, and clean up data (Data wrangling).
These skills are needed to become a Data Engineer:
- SQL/NoSQL
- Cloud platforms
- Java/Scala
- Data Modeling/Data Warehousing
- Python
- Distributed Systems
- ETL tools
- Tableau
- Machine Learning
- Hadoop (HBase, Pig, Hive, MapReduce)
Conclusively, Data Scientists are data miners for clarity of data purpose to consumers while Data Engineers provision infrastructure to enhance data extraction, transfer and load of massive amounts of data.
