As your team grows both horizontally (more people) and vertically (more management levels), new challenges arise. One of the biggest is maintaining alignment across teams without constant meetings and check-ins. Here are a few insights I've gathered: Focus on the roadmap: As a leader, you naturally focus on
reading
With 2021, I have decided to change the way I read. I already have a long list of to-read books in my goodreads account (many of them are actually highly recommended by people I admire) and I have also been setting yearly goals for a good number of years so
Since the start of the pandemic, lots of people have been working outside of their offices and for some of them, this was the first time they have ever experienced it for such a long period. Definitely, this is the largest experiment of remote work that have been ever conducted
Two months ago, I posted about why I think the current situation will change the perspective of many people about remote work. These days we are witnessing a dramatic change coming into effect with companies like Twitter and Facebook spearheading the trend and questioning many of the things we used
Hadoop
Hadoop became an essential componenet of the infrastructure of any company nowadays. There are different distributions maintained and managed by different companies like Cloudera, Databricks and AWS. The distribution managed by AWS is named EMR. This distribution is supposdly fully managed by AWS (Not everything). One of the things that
careem
I still remember when I was very happy to see Souq acquired in 2017 anticipating the potential, this will bring to the region. Now, after the acquisition of Careem, this will create a ripple effect which will isA change the whole region. It won't just open the door
Recently I posted a job post for a machine learning engineer position in my team @ Careem. I got a lot of questions from people who are curious to know more about the position itself, how to prepare for it and what kind of problems does it face ? Data Science vs
clean-code
In this series of posts , I try to share with you some of my highlights on Clean Code Chapters. Lots of people argue about the necessity of applying clean code principles and whether spending time on refactoring is an important step of the software development process or just a waste
data-science
Our minds are always able to comprehend pictures much faster than anything else. Data Visualization can be used for two purposes : 1- Illustration & Presentation Minard's Visualization Of Napoleon's 1812 March which tried to illustrate the cartographic depiction of numerical data on a map of Napoleon&
BigData
Spark is actively supported by Apache Open Source community, and it is used in production by many famous firms and companies. In this blog, the focus would be on productionizing Apache Spark. I will discuss the use cases of Spark and how to enable each of them on production environment.
BigData
Apache Spark On Production (for Data Pipelines) This is the second post about Running Spark On Production, you can read the first post from here In the first post, we talked briefly about spark and then discussed the data exploration use case and compared between the available different tools . In
Hadoop
Hive is a data warehouse system built on top of hadoop for allowing querying and managing data sets. Who ? Hive was created by Facebook and is currently highly adopted by many firms including Netflix, Facebook and Bookings. Why ? Actually not everyone is fond of writing java programs for every problem