An Analytics Engineer job role was never a thing up until 2012. In the pre-era of this role, we only had traditional data teams who worked their tails off in gathering raw data, analyzing it, and transforming it as per the business requirements. The data gets extracted from databases, and Saas tools and then dumped in the data warehouses. Data Analysts used to have loads of requests piled up to gather data and make various dashboards and reports.
Post-2012, the landscape gradually started to transform due to the invention of new data pipeline services, storing data on cloud-based data warehouses and advanced analytics tools like Power BI. The hype for data-related roles started to skyrocket ever since this modernization started with the introduction of DBT and increased data literacy. This is how different roles like Data Analyst, Data Engineer, Analytics Engineer, and so on came into existence.
What is an Analytics Engineer?
An Analytics Engineer is someone who provides scheduled, transformed, and formatted datasets to the users which are then used in the visualization and analysis of data. To put it simply, an Analytical Engineer takes care of tech-oriented work and also business-related work. They also transform, deploy, and document the data.
When making reports and dashboards, an analytical engineer tries to incorporate the best practices of software engineering into the code for better results. This makes the workflow better and produces efficient results.
What is the Role of an Analytics Engineer?
Analytical engineers play an important role in their organizations as they bridge the gap between the tech teams and business teams. These are some of the responsibilities of an Analytical Engineer:
- Information Gathering: The data required is gathered from the data warehouses, it is pre-processed and is kept readily available for further steps or analysis.
- Implementation of Code: Write programs and codes to interpret the data and analyze it.
- Design Data Models: Create a detailed and understandable model about the different data elements used in building the model and how they relate to each other.
- Data Documentation: Every aspect of the entire project that might affect the result must be recorded in detail from time to time.
- Communicate Insights: The results obtained from the research project must be communicated with the stakeholders and clients.
- Collaborate with different teams: The analytic engineers should be flexible enough and be willing to work together with other teams whenever there is a requirement.
- Communicate between the Data team and Business Executives: Communication between the data team and the business executive is crucial as it bridges the gap between technical requirements and business requirements of the project.
What is the Difference Between an Analytics Engineer, a Data Analyst, and a Data Engineer?
The data-related job roles are so confusing because most of the time the responsibilities of those roles overlap and this can be so ambiguous. However, the result or the end product of every job role is different as they have their specific differences which makes them unique.
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| Deliverables | The end output is automated data models. | The end output is the deployed code. | The end output is reports and visualization from which valuable insights are derived. |
Why become an Analytics Engineer?
If you are a data enthusiast who likes to play around with data and turn it into useful information, then this job role would be a perfect fit for you. Being an Analytics Engineer work is not only about working with data but also comes with some jaw-dropping perks:
- Huge Demand: As the data is ever-increasing, the demand for data-related job roles is also highly increasing, and so is the Analytical Engineer. It has been anticipated that the market growth for these roles is going to remain strong.
- Various Opportunities: People in this field can work in numerous companies, from tech to healthcare, advertising to entertainment industries, rookie businesses to ultimately top business companies. Because everyone needs someone to analyze the data and track the progress for them to bring in new changes and more strategic methods to improve the business.
- Salary: Salaries in this field are highly competitive and are based on how specialized the skills of an Analytics Engineer are. Let’s discuss this in detail in the Salary section.
- Work Impact: Analytic Engineers can make a high impact on organizations and businesses with their data-driven decisions that help the businesses make better decisions, optimization, and much more.
What are the Skills Required to Become an Analytics Engineer?
The title “Analytics Engineer” sounds cool, isn’t it? However, having the title is not an impressive achievement and won’t bring a six-figure salary on your plate. It requires a strong skillset and analytical mind. Let’s understand the skills of an Analytics Engineer.
1. Technical Programming
To deal with large sets of data, data transforming process, and data analyzing process, two prominent programming languages are used which are a guaranteed requirement for an Analytics Engineer. They are R and Python. However, Python is used by the majority as it is easy to use and very efficient.
2. Database Language
Apart from the programming languages discussed above, one needs to know a database language to deal with the data stored in the database. Standard Query Language(SQL) is the database language that is widely used to retrieve, update, delete data, make logical data transformations, and write numerous queries for building data models.
3. DBT technology
Knowing DBT is mandatory for any analytics engineer as it is used for data transformation and implementation analysis. The code must be written in SQL.
4. BI tools
Having hands-on experience with Business Intelligence(BI) Tools is always a plus point because it helps in building seamless data pipelines. Power BI, Tableau, and Looker are some of the best-known BI tools.
5. Git Hub
Knowing Version control systems is necessary to be a good analytics engineer as it keeps the logs of the data whenever there happens to be any changes done to the data by multiple users.
Apart from all these technical skills, to become a good analytics engineer one must have strong communication skills, problem-solving skills, inter and intra-personal skills, logical thinking, and business knowledge.
Salary of Analytics Engineer
From the compensation perspective, the analytics engineer job role is super attractive for people looking to make a career in this field as there are only a few people available in the market to carry on this job role which creates a huge demand for it. Let’s see the salary estimates for this job role. For freshers, the average starting CTC would be around Rs 5.8 lakhs per annum. It can vary between Rs 2.2 lakh to Rs 7.5 lakhs per annum depending on the company type and the industry type in India.
For a person with at least 5 years of experience, the salary would be around Rs 9.5 lakhs per annum. Again it can vary between Rs 8 lakh to Rs 18 lakhs per annum depending on the company type and the industry type. In some cases, the CTC might also go up to Rs 23 lakhs per annum depending on the expertise of the person. Remember that these are rough values and not exact compensation, however, one can expect to get compensated in and around these ranges. There is a high chance of getting paid by companies with mature data like Netflix, more than the amount we have discussed here.
Companies that Hire Analytics Engineers
Every organization and company has to make data-driven decisions, so obviously most of them definitely will have the requirement for analytic engineers. Some of the prominent companies or organizations that hire analytic engineers are:
- Netflix
- Uber
- Ola
- IBM
- Airbnb
- Amazon
- Microsoft
- Paytm
- JP Morgan
- Deloitte
- Barclays
- Bank of America
- Flipkart
- Snapdeal
- Accenture Consulting
- KPMG
- Walmart Labs
The companies listed have high requirements for Analytic Engineers as they deal with data. The list doesn’t end here, many other companies and startups also hire Analytic Engineers.
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Conclusion
In conclusion, being an analytics engineer can be a very good option as it has healthy competition, high salaries, and huge demand in the present market and also in the future. As the competition is high, one should upskill oneself continuously as per the market requirements, if not one might fall behind the crowd.
