Senior Analytics Engineer (Job Vacancy)

"Why QS?

At QS, our culture fosters a flexible working environment that encourages our employees to own their career whilst personally and professionally thriving. We collaborate, respect and support each other – and as a company, our values underpin these.

Our mission is to empower motivated people around the world to fulfil their potential through higher education, and to ensure everyone has the same opportunity to achieve that potential. We celebrate the diversity of our teams and believe through sharing our experiences we can learn from one another and become stronger together, which enables us to achieve our goal.

At QS, you’ll be responsible for implementing real change in the international higher education landscape, full of exciting and interesting challenges where you can drive positive impact across the business.

As an Analytics Engineer, this is what you’ll be doing:

As an Analytics Engineer at QS, you will be responsible for creating and maintaining optimal data pipeline architecture in a cloud-based environment and integrated ETL tool, assembling complex data sets, and identifying and implementing process improvements. You will support data analytics projects, optimizing existing processes to improve business outcomes using your technical skills and your strong analytical capabilities. You will also work closely with key business stakeholders to support their data infrastructure needs, while wrapping both new and existing processes with data quality controls and assurance.

The ideal candidate will have strong experience in data analysis, data engineering and management, with expert knowledge of SQL, data transformation in Python and data modelling. You would have good experience in independently understanding code written by others, while able to re-factor and write/document your own code independently. You would have expert Excel skills, with the ability to unravel complex Excel formulas and migrating them into well-documented Python/SQL code within a cloud-based infrastructure.

Role responsibilities:

• Identify, design, and implement internal process improvements, automating manual processes, optimizing data delivery, and re-designing infrastructure for greater scalability. This will be delivered through a mix of Excel files, SQL related databases, Python scripts
• Create and maintain optimal data pipeline architecture in a cloud based ETL tool, using SQL and Snowflake technologies.
• Assemble potentially complex data sets that meet functional and non-functional business requirements.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
• Work with key business stakeholders to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centres and Snowflake/AWS regions.
• Create data tools for analytics and data science team members that assist them in building and optimizing our products/services.
• Work with data and analytics experts to strive for greater functionality in our data systems.

Key skills and experience:

• Strong analytical background, with the ability to manage complex data projects autonomously (Essential).
• Strong Python proficiency, primarily for data transformation and automation (Essential).
• Advanced Excel capabilities with strong capabilities across complex nested formulas, interrelated spreadsheets and formula re-engineering (Essential).
• At least 2+ years of experience as an data engineer, data analyst or similar (Essential).
• Advanced SQL knowledge and experience working with relational databases, query authoring as well as familiarity with a variety of database types (Essential).
• Experience building and optimizing data pipelines, architectures, and data sets.
• Experience working within an Agile environment to deliver based on pre-set milestones.
• Experience building processes supporting data transformation, data structures, metadata, dependency, and workload management.
• Strong data engineering/data management capabilities and experience.
• Some exposure to/understanding of Snowflake/AWS/Azure or other cloud-based infrastructure.
• ETL (Extract, Transform, Load) expertise, both logically and with appropriate tools (e.g Kleene.ai, Talend, Alteryx).
• Experience supporting and working with cross-functional teams in a dynamic environment.
• Cloud and/or Data Migration experience is a plus.
• And any other additional duties as required

Qualifications:

• Bachelor's degree in a STEM field (e.g Mathematics, Statistics, Economics, Computer Science etc)
• Data related qualifications are a plus (e.g MS MCSA, Snowpro Core Certification etc)

Like what you’ve heard? Great, apply now!

As a candidate, we know the application and interview process can be daunting and so it’s important that you have a great experience with us. Our dedicated Talent Team will work hard to ensure you are fully informed at all stages and you are really excited by this opportunity to do meaningful work in the education space.

Equal opportunities

QS Quacquarelli Symonds is proud to be a fair and equal organisation where everyone has the same opportunity to achieve their full potential, irrespective of their background or personal attributes. We celebrate our diversity and believe through sharing our experiences we can learn from one another, be stronger together, and enable our business to thrive.

Why QS?"