Big Data Job Description

Big data is important in various sectors and industries. Big data professionals help stakeholders derive business insights from enormous data stores to enhance data-driven decision-making and improve overall operational efficiency.

No matter the exact nature of the big data job description, professionals working in the big data field utilize a variety of advanced technical techniques and methodologies to sort and analyze data for business purposes. Read on to learn more about big data jobs and the skills involved.

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IBM Data Science

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What is big data?

Big data refers to extraordinarily large, ever-growing data sets so big that normal data management systems can’t handle them. Characteristics of big data include:

• Volume: The enormity of the data sets involved

• Velocity: The speed at which data appears—often in real-time

• Variety: The diversity of data sources

• Veracity: The trustworthiness of certain data sets

• Value: The relevance of data vis-a-vis your particular business needs

Data is unstructured, semi-structured, or structured: 

• Structured data is highly organized and easily understood by machine learning (ML) programs. You parse structured data via a relational database, such as structured query language (SQL). 

• Unstructured data—which is becoming increasingly important in today’s data-driven business world—requires more specialized tools to parse, such as a non-relational database (NoSQL). Companies can collect unstructured data much more quickly and easily than they can structured data, meaning many prefer it to structured data. 

• Semi-structured data is definable as neither fully structured nor unstructured. Common types of semi-structured data include zipped files, emails, web files, XML, and JSON. 

Professionals utilize big data analytics to glean insights from Internet-of-Things (IoT) sensors, social media, smart devices, financial transactions, and other data sources. By incorporating artificial intelligence (AI) and statistical algorithms, big data analysts can create predictive models to forecast business trends. They can also perform what-if analyses, which allow organizations to simulate a variety of scenarios and potential outcomes, all to make better, more informed business decisions. 

Types of big data roles

The amount of big data continues to increase due to advancements in digital technology, such as: 

• Mobility

• Connectivity

• The IoT

• AI

This suggests that a variety of big data-related roles already exist. And they do indeed: Big data applies to fields such as ML, predictive modeling, and data analysis. Big data helps stakeholders in all sorts of businesses, in a variety of industries and sectors, make better data-driven decisions. Types of big data roles include: 

Data engineer

Data engineers develop systems to gather, store, and analyze data. This allows them to help stakeholders make important data-driven business decisions. 

Data engineers aim to make big data: 

• Easy to use: Data should be reliable and intelligible to various end users.

• Comprehensive: Data should come together from across all a business’s data storage sources. 

• Context-based: Data sets should sit amid changing historical trends and show changes over time that reveal patterns.

To become a data engineer, you’ll typically need a bachelor’s degree in computer science, information technology, mathematics, or a related field. The average annual data engineer salary is $106,928 [1]. 

Data scientist

Data scientists develop algorithms to create predictive data models for stakeholders to make better-informed business decisions. 

Data scientists must possess skills in:

• Statistical analysis

• ML

• Computer science

• Programming 

• Data storytelling

Many data scientists have a master’s degree in data science or data analytics, with a strong foundation in mathematics and computer science. The average salary for these professionals is $119,684 per year [2]. 

Big data analyst

Big data analysts extract actionable information from big data sets. They help stakeholders make data-driven business decisions based on historical patterns in enormous reams of data. 

Big data analysts help businesses optimize and improve performance, discover patterns in data, and better determine what customers want. 

Big data analysts need a bachelor’s degree in mathematics, statistics, economics, or data analytics. They make an average of $86,622 annually [3]. 

Hadoop developer

Hadoop developers develop, operate, and troubleshoot applications that interact with Hadoop. Hadoop is an open-source Apache program that allows you to process and manage big data, including structured, semi-structured, and unstructured data, regardless of format. 

Hadoop developers do what many other big data-centric employees do: They track and analyze big data, then convert it into designs that allow stakeholders to understand how to make the best possible data-driven business decisions.

In addition to extensive knowledge of Hadoop itself, Hadoop developers usually have knowledge of: 

• Hadoop components such as HBase, Pig, Hive, Sqoop, Flume, and Oozie

• Back-end programming

• Coding languages

• SQL

• HiveQL

• Concepts such as multi-threading and concurrency

Hadoop developers usually need a bachelor’s degree in analytics, electronics, statistics, or a related field. The average annual Hadoop developer salary is $94,663 [4].

Essential big data skills

Big data skills remain in demand, and the need for skilled big data workers will likely increase. Essential big data skills include both technical and non-technical skills. 

Technical skills

To work in big data, you’ll need to have a solid grasp of:

• Cloud computing platforms, including Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP)

• Programming languages, such as Python, Java, or Scala

• Relational databases, such as SQL 

• Big data frameworks, such as Hadoop, Apache Spark, and Apache Kafka

• Extract, transform, load (ETL) tools.

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Generative AI for Data Scientists

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Non-technical skills

Big data professionals must also possess certain non-technical or workplace skills, such as: 

• Communication

• Problem-solving

• Teamwork

Big data professionals must also be organized, be able to make informed decisions, and have an understanding of business opportunities and relevant risk management protocols. 

Industry variations in the big data role

Big data roles exist in a variety of industries and sectors, such as: 

• Health care

• Finance

• Marketing

Regardless of the field you work in, you’ll help companies parse big data to gain insight into the behavior of customers and clients, personalize targeted marketing campaigns, and apply predictive analysis to a variety of tasks—such as helping customers make better-informed financial decisions or developing new drug therapies. 

Learn more about big data job descriptions with Coursera.

Big data remains important across many industries and sectors, and therefore, big data professionals of all sorts are in high demand. 

Learn more about big data with Coursera. Look into the University of California, San Diego’s Introduction to Big Data course. Then, expand your knowledge with Google Cloud’s Big Data and Machine Learning Fundamentals. When you’re ready, consider earning your Data Analyst Professional Certification from Meta.

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Meta Data Analyst

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