This test is split into 5 sections:
- Data Pipelines
- Databases
- System Design
- Charts & APIs
- Machine Learning
Please create a Github repository containing your submission and send us an email containing a link to the repository.
Dos:
- Frequent commits
- Descriptive commit messages
- Clear documentation
- Comments in your code
Donts:
- Only one commit containing all the files
- Submitting a zip file
- Sparse or absent documentation
- Code which is hard to read
An e-commerce company requires that users sign up for a membership on the website in order to purchase a product from the platform. As a data engineer under this company, you are tasked with designing and implementing a pipeline to process the membership applications submitted by users on an hourly interval.
Applications are batched into a varying number of datasets and dropped into a folder on an hourly basis. You are required to set up a pipeline to ingest, clean, perform validity checks, and create membership IDs for successful applications. An application is successful if:
- Application mobile number is 8 digits
- Applicant is over 18 years old as of 1 Jan 2022
- Applicant has a valid email (email ends with @emailprovider.com or @emailprovider.net)
You are required to format datasets in the following manner:
- Split name into first_name and last_name
- Format birthday field into YYYYMMDD
- Remove any rows which do not have a name field (treat this as unsuccessful applications)
- Create a new field named above_18 based on the applicant's birthday
- Membership IDs for successful applications should be the user's last name, followed by a SHA256 hash of the applicant's birthday, truncated to first 5 digits of hash (i.e <last_name>_<hash(YYYYMMDD)>)
You are required to consolidate these datasets and output the successful applications into a folder, which will be picked up by downstream engineers. Unsuccessful applications should be condolidated and dropped into a separate folder.
You can use common scheduling solutions such as cron or airflow to implement the scheduling component. Please provide a markdown file as documentation.
Note: Please submit the processed dataset and scripts used
You are the tech lead for an e-commerce company that operates on the cloud. The company allows users to sign up as members on their website and make puchases on items listed. You are required to design and implement a pipeline that processes membership applications and determine if an application is successful or unsuccessful. Applications are dropped into a location for processing. Engineers have already written code to determine a successful or unsuccessful application, as well as creating membership IDs for successful applications. You may use the processed datasets from section 1 as reference. Successful applications should be sent to a location for storage and refrence.
The e-commerce company also requires you to set up a database for their sales transactions. Set up a PostgreSQL database using the Docker image provided. We expect at least a Dockerfile which will stand up your database with the DDL statements to create the necessary tables.vYou are required to produce entity-relationship diagrams as necessary to illustrate your design, along with the DDL statements that will be required to stand up the databse. The following are known for each item listed for sale on the e-commerce website:
- Item Name
- Manufacturer Name
- Cost
- Weight (in kg)
Each transaction made by a member contains the following information:
- Membership ID
- Items bought
- Total items price
- Total items weight
Analysts from the e-commerce company will need to query some information from the database. Below are 2 of the sameple queries from the analysts. Do note to design your database to account for a wide range of business use cases and queries. You are tasked to write a SQL statement for each of the following task:
- Which are the top 10 members by spending
- Which are the top 3 items that are frequently brought by members
We will be referencing the database from Section2 in this design.. This database will be used by several teams within the company to track the orders of members. You are required to implement a strategy for accessing this database based on the various teams' needs. These teams include:
- Logistics:
- Get the sales details (in particular the weight of the total items bought)
- Update the table for completed transactions
- Analytics:
- Perform analysis on the sales and membership status
- Should not be able to perform updates on any tables
- Sales:
- Update databse with new items
- Remove old items from database
You are designing data infrastructure on the cloud for a company whose main business is in processing images.
The company has a web application which allows users to upload images to the cloud using an API. There is also a separate web application which hosts a Kafka stream that uploads images to the same cloud environment. This Kafka stream has to be managed by the company's engineers.
Code has already been written by the company's software engineers to process the images. This code has to be hosted on the cloud. For archival purposes, the images and its metadata has to be stored in the cloud environment for 7 days, after which it has to be purged from the environment for compliance and privacy. The cloud environment should also host a Business Intelligence resource where the company's analysts can access and perform analytical computation on the data stored.
As a technical lead of the company, you are required to produce a system architecture diagram (Visio, PowerPoint, draw.io) depicting the end-to-end flow of the aforementioned pipeline. You may use any of the cloud providers (e.g. AWS, Azure, GCP) to host the environment. The architecture should specifically address the requirements/concerns above.
In addition, you will need to address several key points brought by stakeholders. These includes:
- Securing access to the environment and its resources as the company expands
- Security of data at rest and in transit
- Scaling to meet user demand while keeping costs low
- Maintainance of the environment and assets (including processing scripts)
You will need to ensure that the architecture takes into account the best practices of cloud computing. This includes (non-exhaustive):
- Managability
- Scalability
- Secure
- High Availability
- Elastic
- Fault Tolerant and Disaster Recovery
- Efficient
- Low Latency
- Least Privilege
Do indicate any assumptions you have made regarding the architecture. You are required to provide a detailed explanation on the diagram.
Your team decided to design a dashboard to display the statistic of COVID19 cases. You are tasked to display one of the components of the dashboard which is to display a visualisation representation of number of COVID19 cases in Singapore over time.
Your team decided to use the public data from https://documenter.getpostman.com/view/10808728/SzS8rjbc#b07f97ba-24f4-4ebe-ad71-97fa35f3b683.
Display a graph to show the number cases in Singapore over time using the APIs from https://covid19api.com/.
Note: please submit screenshots of the dashboard
Using the dataset from https://archive.ics.uci.edu/ml/datasets/Car+Evaluation, create a machine learning model to predict the buying price given the following parameters:
Maintenance = High
Number of doors = 4
Lug Boot Size = Big
Safety = High
Class Value = Good