Data engineering is one of the fastest growing and most in-demand jobs in tech today. With data becoming an increasingly important asset for companies across all industries, the need for skilled data engineers who can build data pipelines, infrastructure, and analytics systems is skyrocketing.
What is a data engineer?
A data engineer is responsible for designing, building, and maintaining the infrastructure that allows data scientists and analysts to do their work. Their primary duty is to create data pipelines that take data from source systems, transform and clean the data, and load it into databases and data warehouses for analysis.
Data engineers need a strong foundation in computer science, statistics, and mathematics along with knowledge of tools like SQL, Python, Spark, Kafka, Airflow, and cloud platforms like AWS, GCP, and Azure. Their work spans both software engineering and data analytics.
Why is there increasing demand for data engineers?
Here are some of the key reasons driving the high demand for data engineering skills today:
- Data volume is exploding – With the rise of IoT devices, social media, ecommerce and more, the amount of data companies capture and analyze for business insights is growing exponentially. Data engineers build the foundations to store and process all this information.
- Need for real-time data and insights – Companies today want to make data-driven decisions as quickly as possible. Data engineers create streaming pipelines and infrastructure like data lakes and warehouses to enable real-time analytics.
- Shift to cloud computing – Migrating data and analytics to the cloud is a top priority for most companies today. Data engineers are critical for running databases, data lakes, warehouses and other data platforms in public cloud environments.
- Growth of AI and machine learning – Training machine learning models requires massive amounts of data. Data engineers construct the data pipelines to feed data to ML models.
- Rise of data science teams – As companies build out data science teams to derive value from data, data engineers provide the foundational data infrastructure these teams need to function.
In essence, data engineering is a central capability for any data-driven organization today. As data volumes and the strategic importance of data analytics grow, demand for data engineers will continue rising.
Data engineer job growth statistics
Here are some key statistics that demonstrate the soaring demand for data engineers:
- LinkedIn???s 2020 Emerging Jobs Report listed Data Engineer as the #4 emerging job for 2020. LinkedIn saw data engineer job listings grow 33% annually from 2015 to 2019.
- Glassdoor???s 2020 Best Jobs in America report ranked Data Engineer #9 on its list, citing a median base salary of $108,000 for the role.
- According to Indeed data, data engineer job postings grew 64% from 2017 to 2019 in the US.
- Burning Glass Technologies reported in 2019 that demand for data engineers grew 367% between 2013 and 2019.
Clearly, data engineer roles are rapidly multiplying across practically every industry as organizations invest heavily in data analytics capabilities.
Data engineer salary trends
Along with a high volume of job openings, data engineering also commands very competitive salaries. Here are some key data points on data engineer compensation:
- According to Glassdoor, the average data engineer salary in the US is $105,462. In major tech hubs salaries can reach $150,000 and up.
- PayScale reports the average data engineer salary at $92,007 in the US. Experienced data engineers can earn over $130,000.
- LinkedIn lists the average data engineer salary in the San Francisco Bay Area at $146,730.
- According to Indeed, the average data engineer salary in New York City is $123,541.
- Dice???s 2020 Tech Salary Report puts the average data engineer salary at $106,000 for those with 5-9 years of experience.
Given the rapid growth in demand for data engineers, salaries are likely to continue rising as companies compete for talent. The most skilled data engineers working in top tech firms can command total compensation packages worth $200,000 or more.
High industry demand across technology and finance sectors
While data engineers are in demand across many industries, some of the highest demand originates from:
- Technology – Major technology and software companies need large numbers of data engineers to build and maintain data pipelines and analytics systems at massive scale. Top companies hiring data engineers include Facebook, Google, Amazon, Microsoft, Uber, Airbnb and more.
- Finance and fintech – Banks, hedge funds, insurance firms, and other financial service providers rely on data analytics and thus need strong data engineering talent. The explosion of fintech companies over the past decade has also driven demand.
- Consulting and professional services firms – Large consulting firms and IT services companies maintain dedicated data engineering practices as they help clients build data capabilities. McKinsey, Deloitte, Accenture, and Cognizant all employ sizable data engineering teams.
- Retail and ecommerce – Major retailers like Walmart and Amazon have huge volumes of data and need data engineers to manage data pipelines and build analytics applications.
- Healthcare – Data engineers are playing a growing role in healthcare as providers adopt data-driven insights to improve patient outcomes and manage costs. Major providers and payers need data engineering talent.
Essentially, demand for data engineers stems from any large enterprise leveraging data analytics today. Even traditionally slow moving industries like manufacturing and logistics are ramping up hiring.
Data engineering skills in high demand
To capitalize on the booming demand, it???s important for aspiring data engineers to build expertise in the key skills most sought after by employers today:
- AWS/GCP/Azure – Ability to build data solutions leveraging major cloud platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP) and Microsoft Azure.
- SQL and NoSQL databases – Expertise working with relational databases like PostgreSQL, MySQL, and non-relational databases like MongoDB, Cassandra, etc.
- Python and Java – Proficiency in Python for ETL and data science applications or Java for building distributed data engineering systems.
- Hadoop, Spark, Kafka – Experience with distributed data processing frameworks like Hadoop, Spark, and Kafka.
- Data modeling – Ability to model data and relationships between different data sources and systems.
- Data warehousing – Knowledge of data warehousing systems like Snowflake, Redshift, and BigQuery for analysis.
- CI/CD and DevOps – Familiarity with continuous integration / continuous delivery and DevOps practices for deploying and monitoring data engineering systems.
- Containerization – Knowledge of Docker and Kubernetes for containerizing data solutions in the cloud.
Mastering the above skills can set data engineers up for success in today???s job market. Ongoing learning is also crucial as new tools and technologies emerge.
How to start a career as a data engineer?
For those looking to break into a data engineering career, here are some tips:
- Learn in-demand skills like Python, SQL, AWS, Spark, etc. Take online courses to build expertise.
- Get hands-on experience via personal projects, open source contributions, or internships.
- Earn a master???s degree in computer science or data science to gain advanced technical skills.
- Consider data engineering certifications from AWS, GCP, Cloudera or other providers.
- Build a portfolio highlighting your work on data pipelines, ETL processes, databases and other relevant projects.
- Network with data engineers and recruiters at local meetups and industry events.
- Target entry-level data engineering or data analyst roles at tech companies to get your foot in the door.
- Keep your skills fresh. Learn new data tools and stay on top of industry advancements.
With the right skills and strategy, there are abundant opportunities to break into data engineering roles right now.
Conclusion
In summary, demand for data engineers continues rising steeply as organizations invest heavily in data platforms and analytics. Data engineers command competitive salaries and have their pick of job openings at leading tech firms and Fortune 500 companies. For technologists looking to take advantage of one of tech???s hottest careers, building the right data engineering skills can unlock huge opportunities. The demand for data engineers shows no signs of slowing down anytime soon.