Analytics Engineer: Job Description, Skills, Salary, & Responsibilities
As technology advances each day, the field of analytics engineering is growing rapidly. Analytics engineers collect data, extract insightful information, and provide a clear understanding of how data can be used to advance a company toward its goals. As a profession, analytics engineering dynamically fuses technical expertise with business acumen to design, develop, and maintain the data infrastructure necessary for analytics. Are you interested in a career in analytics engineering? In this article, we’ll review the role of an analytics engineer, the job responsibilities, and the skills needed to succeed in this role.
In this article:
- The Role of an Analytics Engineer
- Job Responsibilities for Analytics Engineers
- Educational Requirements for Analytics Engineers
- Skills Needed to Excel in Analytics Engineering
- Salary Information for Analytics Engineers
The Role of an Analytics Engineer
“Data is a tool for enhancing intuition.”
– Hillary Mason, Data Scientist and Founder of Fast Forward Labs
Analytics Engineers are professionals who are tasked with designing, constructing, and maintaining the robust technical infrastructure needed for data analysis. Analytics engineers work closely with business professionals, data scientists, and analysts to collect and organize data, as well as, develop data visualization tools.
Analytics engineers are integral to the establishment of integrated data models and the development of data storage and processing systems.
Job Responsibilities for Analytics Engineers
“Information is the oil of the 21st century, and analytics is the combustion engine.”
– Peter Sondergaard, Sr. Vice President & Global Head of Research at Gartner, Inc
Analytics engineers play a dynamic role in a business’ success. However, there is no one-size-fits-all job description for those working in analytics engineering. The specific responsibilities of an analytics engineer will vary depending on the company one works for – after all, some organizations require complex data transformations and others do not. However, there are some key duties that most analytics engineers carry out.
Many folks working in analytics engineering are responsible for the following:
- Collaborating with cross-functional teams and other data professionals to define business goals and set parameters to measure analytics outcomes
- Working with data scientists and analytics to collect and clean data for analysis
- Designing data models, as well as, developing and maintaining data pipelines
- Creating and maintaining data storage systems
- Developing documentation for data pipelines and storage systems
- Developing software to implement data reporting
- Troubleshooting and debugging data system errors
- Embracing new technology and staying up to date with industry best practices to continuously improve data analysis skills
Educational Requirements for Analytics Engineers
The educational requirements for analytics engineers will vary depending on the specific job you land. However, some common educational requirements may include a bachelor’s degree in a tech field such as information technology, computer science, statistics, software development, or data science. More advanced roles may require a master’s degree in a related field of study and a Ph.D. may be desired for advanced research positions.
While many organizations look for candidates with formal education, many others do not – which helps level the playing field for applicants who lack formal backgrounds but have a wealth of experience and knowledge around analytics engineering.
Certification Programs for Those Interested in Data
In addition to formal education, there are several online certification programs available for those interested in learning more about analytics engineering. Some popular certification programs include:
- Cloudera Certified Data Engineer: a certification program designed for folks who design, develop, and maintain data systems using Cloudera’s platform.
- Data Engineering on Google Cloud Platform: an educational course created for individuals who design and maintain data processing systems using Google Cloud Platform.
- AWS Certified Big Data – Specialty: a course designed for people who create, build, and maintain data systems using Amazon Web Services (AWS).
- Data Science Council of America (DASCA): a professional organization that offers a variety of certifications for data scientists, analytics engineers, and other professionals who work with data.
Skills Needed to Excel in Analytics Engineering
“Data analytics is the future, anfd the future is NOW! Every mouse click, keyboard button press, swipe or tap is used to shape business decisions. Everything is about data these days. Data is informaiton, and information is power.”
– Radi, Data Analysts at CENTOGENE
Like many professionals that work with data, analytics engineers need to hone a variety of soft and hard skills to succeed in their roles. Below, are a few of the skills analytics engineering requires:
- Strong programming capabilities: Analytics engineers should have an in-depth understanding of computer programming concepts and be proficient in a programming language such as Python or R.
- Efficient problem-solving and analytical skills: Analytics engineers need to be able to analyze data effectively and troubleshoot data issues as they arise.
- Database management and data modeling skills: Knowledge of database management and modeling data is integral to analytics engineering. Additionally, becoming familiar with SQL and NoSQL databases may come in handy.
- Data warehousing and ETL: In-depth understanding of data warehousing concepts, as well as, experience with ETL (extract, transform, load) tools and processes is essential to designing data pipelines.
- Cloud computing: An understanding of cloud computing platforms such as AWS and Azure may be important for building and maintaining data storage systems.
- Machine learning: Knowledge of machine learning concepts helps analytics engineers effectively collaborate with data scientists and data analysts.
- Strong communication skills: Analytics engineers need to be able to effectively communicate with cross-functional teams of people, including data scientists, data analysts, product designers, IT teams, and other business professionals.
Salary Information for Analytics Engineers
The amount of money an analytics engineer in the United States earns depends on many factors, including geographic location, level of experience, and the specific industry one works in. However, according to Glassdoor and Salary.com, the average salary for an analytics engineer is around $110,000 per year.
For entry-level positions, the starting salary is a bit lower and tends to be around $80,000 per year. While more senior positions garner more funds and can be paid over $125,000 annually. Outside of experience being a factor, industry plays a huge role in determining an analytics engineer’s salary – with those working in tech and finance earning significantly higher salaries than folks in other industries.
According to the Bureau of Labor Statistics (BLS), job opportunities for those interested in working with data will continue to grow in the coming years. The BLS projects that the operations research analysts industry, in which analytics engineering is classified, will see a growth of 25% between now and 2030 – making it a viable career option for those looking to enter a new field or expand their careers.