Big Data Engineer: Career Guide

What does a Big Data Engineer do?

Big data engineers design and manage systems that process large volumes of data. You work on building scalable data architectures, ensuring data is collected, stored, and processed efficiently for business insights.

Key duties & responsibilities

Big Data Engineers in the IT & Development field handle essential tasks and contribute significantly to achieving team and organizational goals. Here are some of their primary responsibilities:

• Design, construct, install, test, and maintain highly scalable data management systems.
• Ensure systems meet business requirements and industry practices.
• Integrate new data management technologies and software engineering tools into existing structures.
• Create high-performance algorithms, prototypes, predictive models, and proof of concepts.
• Research opportunities for data acquisition and new uses for existing data.
• Develop data set processes for data modeling, mining, and production.
• Recommend ways to improve data reliability, efficiency, and quality.
• Collaborate with data architects, modelers, and IT team members on project goals.

How to become a Big Data Engineer

Launching a career as a Big Data Engineer requires a specific education. We outline the essential qualifications, skills, and steps to enter this field.

Qualification

• Bachelor’s degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field. Master’s preferred.
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift.
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Knowledge of machine learning and artificial intelligence is advantageous.

Requirements & skills

• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
• A successful history of manipulating, processing, and extracting value from large disconnected datasets.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.

Big Data Engineer salary guide

Wondering what Big Data Engineers earn? Explore salary ranges by experience, and career tips to maximize your earning potential.

Job	Branch	Avg. US salary
Big Data Engineer	IT & Development	124,000 USD

The average salary for a Big Data Engineer in the U.S. is approximately $124,000 per year and can vary from entry-level to senior positions. Big Data Engineers may receive a wide range of benefits.

Big Data Engineer salary career steps

Level	Experience	Avg. salary per year
Entry Level	0-2 years	$93,000
Mid Level	3-5 years	$111,600
Experienced	6-10 years	$124,000
Senior	11+ years	$136,400
Veteran	20+ years	$155,000

Sources: U.S. Bureau of Labor Statistics, Payscale, expert interviews

How to advance your career

Big Data Engineers can progress to senior data roles such as Senior Data Engineer or Chief Data Officer. They may also transition into data architecture, machine learning engineering, or data science roles. As their expertise grows, they might lead teams or departments, focusing on strategic data initiatives and innovations.

Typical work environment

Big Data Engineers typically work in an office environment but may also work remotely. They often collaborate with data scientists, business analysts, and IT team members to refine data usage and enhance data systems. Their work can require long hours, especially when deploying new systems or troubleshooting existing ones.