I. What is the client’s business?

Our client is a UK-based research firm providing English-medium K-12 international school data. It provides the most comprehensive, current, and objective intelligence to international schools worldwide.

II. Why did the client need a Data Engineer?

As the leading supplier of intelligence for international schools, our client relies heavily on data to develop its products and services. 
With a growing database and increasingly complex demands for insightful and actionable intelligence, it became evident that their data architecture required a specialized touch. 

Here are the key reasons why the client partnered with MultiplyMii to hire a remote Data Engineer:

• Data Integration and Transformation: The client collects data from a variety of sources, and integrating this into a cohesive, usable format presented a significant challenge. A dedicated Data Engineer was required to establish efficient ETL (Extract, Transform, Load) processes.

• Advanced Reporting and Visualization: To stay competitive and provide unmatched value to its clients, the company needed advanced data visualization and reporting capabilities.

• Accuracy and Integrity: As the data is central to the client’s products and services, data accuracy and integrity is crucial to the business. A Data Engineer is essential to monitor, validate, and clean the data.

Hiring a skilled Data Engineer through MultiplyMii has allowed the client to build and maintain a data infrastructure. It is not only robust and reliable; it is also flexible and primed for growth, positioning the company to continue as a leader in its field.

III. How much is the hired candidate’s salary?

Carrie, the hired Data Engineer, earns a monthly salary of $1,600 inclusive of standard Philippine employment benefits.

IV. What are the hired employee’s responsibilities?

Carrie plays a critical role in our client's mission to provide comprehensive and current intelligence to international schools. This specialist is the architect behind the data structures that power the client's extensive and valuable insights.

She was entrusted with these responsibilities:

• Data Pipelines: Regularly creating and updating efficient pipelines to transform and load data from various sources into the company’s data warehouse.

• Data Models and Schema Designs: Crafting optimized data models and schema designs that streamline data querying and analysis.

• ETL Process Design and Maintenance: Using SQL, Python, or other relevant tools to develop and sustain ETL processes supporting data integration.

• Data Architecture: Collaborating with the development team to guarantee that the data architecture is not only robust but also poised for growth and adaptability.

• DevOps Best Practices Implementation: Ensuring the data solutions are developed and deployed in line with DevOps standards, including a seamless CI/CD pipeline.

Now that Carrie is on board, the organization’s data infrastructure is more than a technical asset; it is a strategic tool. 
Our client can trust that the integrity, accessibility, and reliability of their data are expertly managed, allowing them to focus on leveraging those insights to serve their own clients better.

V. What was the hired candidate’s work background?

With a solid foundation in Data Engineering, Carrie brought extensive expertise and a proven track record to the table:

• 5 years of experience in Data Engineering, specializing in ETL processes from various data sources using API, Python, and SQL

• Proficiency in integrating and transforming data into unified datasets for advanced dashboarding and data analysis

• Extensive experience with Business Intelligence tools, including Power BI, Hubspot Report, and Cognos BI

• Agile methodology practitioner, showcasing adaptability and responsiveness in fast-paced environments

• History of close collaboration with stakeholders, Iteration Managers, and Squad Leaders, demonstrating excellent communication and team skills

• Track record of creating ad-hoc reports and automating processes to meet the dynamic needs of the team and projects

With this rich background, the candidate was not just experienced but ideally suited to navigate the complex data landscape of our client's international school intelligence platform.