What do you do at BI:PROCSI ?

I am a Senior Data Engineer working on a large size client project. Work involves anything around gauging the value of data or making use of data more efficiently. These include finding the best way to optimise query performance on a very large dataset, data modeling, architecting data pipeline and orchestration so that the data will be fed into the client’s data science and analytics platforms. I also worked on projects involving DevOps and data infrastructure. More to be coming related to machine learning/data science and AI.

Another part of the job also involves a lot of client interaction, handling different kinds of requests from clients and architecting the best solutions for them.

What do you enjoy most about working at BI:PROCSI?

The team is very supportive of each other and will not let anyone fail. The management gives a lot of trust and flexibility in how we approach work. We have new challenges every day and endless opportunities for you to cultivate your skillset. The training opportunities are great here, and the company always encourages learning and development, both in terms of technical and soft skills. Of course, if you like to step out of your comfort zone and work on something new, or you like to wear multiple hats. This could be the place for you as this happens quite often during daily work.

What made you choose BI:PROCSI over other companies you were considering?

BI:PROCSI has a healthy growth of project and client base. You will have opportunities to contribute a few of them. As engineers, you will also have a chance to contribute to the sales process in different ways. The management is relatively transparent and happy to listen to feedback and take action on it.

What skills or experiences have you gained since joining the company?

Despite the fact that I have not been here for long, I have gained tons of experience and harnessed some of the skills I had before. I have been working extensively on Azure DevOps Pipelines and Data Factory. Built different data orchestration platforms using the advanced features of Airflow. Achieved multiple-fold performance optimisation in ELT processes in Snowflake. Worked on IaC projects using Terraform. I can see more and more coming, especially in AI/LLM-related work.

How would you describe the company's culture and values?

It is a culture of learning and stepping out of your comfort zone. Also, everyone enjoyed collaborating with each other when facing challenges. We like supporting each other to make sure everyone achieves their full potential.

Can you share a favourite piece of advice(s) or a lesson(s) you've learned during your career?

During my career, I have been wearing multiple hats. I was a developer, machine learning engineer, a consultant, a data scientist and a data engineer. I worked in fintech, investment banks, tech startups and consultancies. We should always be open-minded and happy to learn about the business domain you are working in. The technology landscape changes fast, and we should aim to make ourselves polyglot and generic problem solvers. Instead of a “I know/am comfortable with this skill/technology, so the problem should be best solved in this way” mindset, you should be thinking “This is a challenging problem, and I need to learn or use this skill because it is the best for the problem”.

Always question yourself when learning new tech (or following a hype): How can we make business sense out of it or create value from it? How will it best fit in the current picture of your project, and how will this move forward? Take a step back and consider the strategic implications of any technical decision you want.

Also work on improving your soft skills during your daily job, such as project management skills, sales and marketing skills. The “human element” of engineers will stand out in the era of AI advancements.

Can you share any advice for individuals who are considering joining BI:PROCSI?

Be prepared to learn a lot, both in soft skills and technical skills. Be curious and be adaptive to fast pace daily work.