You’re looking for a data analytics job. How can you find the right one?

Before applying decide the domain and roles you're interested. Connect with the people in the roles you're interested in and start asking for referrals and guidance to reach your desired position.

Before applying for a job, think about this: - In which area do you identify most: data analytics, data science, data engineering. - What do you already know and what would you like to learn? - Is there any specific technology you would like to work with? - Do you identify as an individual contributor or as a leader?

To find the right data analysis job: - Clearly define your goals and interests. - Research companies and industries that value data analysis. - Take advantage of professional networks, such as LinkedIn and specialized groups. - Apply to positions that align with your skills and aspirations. - Highlight your technical skills and relevant experience in your resume and interview. - Consider internship or freelancing opportunities to gain experience. - Be open to learning and growing in your chosen role.

Researching companies is crucial when seeking a data analytics job. Investigate their industry standing, culture, and values to ensure they align with your career goals. Examine their analytics projects and the technologies they use, matching these with your expertise and learning interests. Reading reviews on platforms like Glassdoor offers insights into the work environment and progression paths. Networking with current or former employees can provide insider views. This research ensures you're well-informed and the company fits your professional aspirations.

- Research potential data analytics job opportunities by examining company missions, values, and products. - Explore how companies utilize data analytics to achieve objectives and their expectations for data analysts. - Gather information on benefits, challenges, and opportunities of working at each company through various sources like websites, social media, and online reviews.

It is essential to research the company before applying for the job. - Has the company been financially healthy in recent years? - Do the company's objectives make sense to you? - Does the stack used interest you? - How does this company's career ladder work?

There are several ways to demonstrate your skills: - Keep your CV and LinkedIn profile updated and user-friendly. - Have a solid portfolio demonstrating your main skills. - Get official certifications for the technologies you use.

If a company has caught your attention, don't be shy about contacting employees in data roles, this can be beneficial in several ways: - There is no better way to understand a company's culture than talking to its employees. - A better understanding of the use of technologies and stack. - Network consolidation: if a job comes up in the future, people may remember you and invite you for an interview.

To better prepare for an interview, try to research a little about the company. - Try to find out what challenges the company currently faces. - What technologies are used by the company. - Demonstrate how your knowledge can help the company solve these challenges. - Don't forget to mention success cases of your projects from previous companies, if it's your first interview, show them your portfolio!

Context is important. The day to day of a data analyst in the finance sector and a data analyst in education is very different. It's important to consider this as you explore the job market. I, for example, am much more interested in working with data that is relatively closely linked to human activity (education, communication, marketing, customer success, etc.) than I am in working with data that is more divorced from human activity (finance, energy,etc.). Every data analyst will have their own scope of interest and it's important to reflect upon this and keep it in mind.

I want share an advice for FRESHERS, since there is there is a gap in the industry standards demand and supply of data folks meaning knowing sql, python tableau is just not enough. Please do some industry standards projects very diligently, simulate yourself as a analyst and understand the nuances and data as if companies progress depends upon the project. Be a problem solver not just the data analyst, learn to work on other trivial business problems and process, innovate how processes can get better, here is where small efforts takes you big distance. Spend time and understand domain, then switch. Get a deep understanding of domain knowledge and select that appeals to you most, then strive for specialisation.

- Master the basics! Having a solid foundation of the basics is essential. Currently: SQL, Python, English. - It's all about the business! Don't be shy about diving into the business, even if you're the lone wolf coder type, knowing what drives the company will greatly improve your work. - Don't forget your soft skills! If you are a great technical professional, you have to be able to present and explain your work to other people. So, focus on communication, presentations and public speaking.