Top Skills and Strategies for Data Engineers

The growing digital ecosystem has contributed to the rise of data which has now become a vital aspect of every organization worldwide. As reported by Statista, the amount of global data created and consumed in 2020 was 64.2 zettabytes which is expected to rise to 180 zettabytes by 2025.

With the rapid rise in data production and consumption, data engineering has emerged as the tool to bridge the gap between a wide array of raw data and actionable information and patterns. Data engineers demystify large amounts of data and play a pivotal role in the modern digital landscape with top data engineer skills such as programming, coding, data analysis, and knowledge of various database tools.

If you are an aspiring data engineer, read on to know more about the skills and competencies you need to build a successful career in the data industry.

 What are the roles and responsibilities of a data engineer?

Data engineers are valuable assets of an organization and play a crucial role in the maintenance of the data pipeline. The collection, storage, processing, and analysis of data are the responsibility of a data engineer whose primary focus is on the accessibility of data.

Here are some of the roles and responsibilities of a data engineer:

• Development and maintenance of database architecture and other data processing systems to get easy access to large amounts of raw data.
• Building data pipelines to transfer data from one source to another.
• Extract, transform, and load (ETL) data ensuring its consistency to help data scientists and analysts do their duty.
• Develop various data quality metrics to ensure the quality of data throughout the data cycle and perform various cleansing processes to remove any anomalies.

To perform these responsibilities daily, you must have several data engineer skills that will help you carry out these functions perfectly.

The Canadian College of Technology and Business (CCTB), Vancouver offers a post-secondary diploma program in data engineering and analytics which will help you acquire the skills essential to succeed as a data engineer in a competitive job market. The co-op program is designed to impart academic and practical knowledge to all the students who enroll in the full-time diploma.

The program includes topics such as information systems management, relational database systems, SQL, data structure, system design, machine learning, warehousing concepts, and other important topics in data analysis. This will prepare you for a rewarding career in the professional data industry.

What are the Top Data Engineer Skills?

In today’s digital age, there is a high demand for skilled data engineers across various organizations. Possessing these necessary skills will help you land a job role in the industry and build a fruitful career. Here are some of the top skills required to become a data engineer:

Knowledge of programming languages

Programming and coding skills are an absolute necessity when it comes to any job in the data industry. You must have good knowledge of various programming languages that are commonly used in the data industry to build a successful career as a data engineer.

A solid foundation in Python, Java, C++, SQL, Scala, and R will enable you to develop data pipelines and transform data.

ETL (Extract, Transform, Load) process proficiency

ETL proficiency is a top data engineer skill and one of the fundamentals to work in this sector. The ETL process includes extracting data from various sources, transforming it into suitable formats, and loading it into target systems for further analysis.

Data Warehousing and Processing

A data engineer must be well-versed in various data storage techniques and should be able to develop efficient data storage mechanisms. You must also have basic knowledge of various data warehousing tools and techniques such as data marts and data lakes.

As a data engineer, you must also be familiar with various relational databases (e.g., MySQL, PostgreSQL), NoSQL databases (e.g., MongoDB, Cassandra), data warehouses (e.g., Amazon Redshift, Google Big Query), and distributed computing frameworks (e.g., Apache Hadoop, Apache Spark).

Data Governance

Data engineers must have in-depth knowledge of data governance practices. You should possess knowledge of data privacy regulations and implement appropriate security measures to protect sensitive data. This includes data access controls, encryption, anonymization techniques, and monitoring tools for identifying potential security breaches.

Apart from these primary skills, data mining, visualization, cloud computing, machine learning, and knowledge of several data structures are required to make you a competent data engineer.

Enroll in a data engineering program to learn these skills and become a successful data engineer.

Click here to learn more!

Sources: Statista LinkedIn Coursera