Intermediate Analytics Engineer at Valenture Institute

Who Are We, The Data And Analytics Team?

• The Data and Analytics Team is a central node of Valenture Institute that supports the data and analytics needs for the entire business. Our team exists to improve data-driven decision making across many stakeholders, to increase the operational effectiveness of teams, and to improve the core educational experience of Valenture’s educational products by building data assets, insight assets andprediction assets.

Who Are You?

• As an intermediate analytics engineer, you possess a strong foundation in data engineering and analytics, demonstrating a passion for leveraging data to drive actionable insights.
• You thrive in anticipating and addressing business stakeholders’ evolving needs and excel in crafting compelling narratives through data visualisations.
• Your commitment to making a tangible impact in education is evident in your entrepreneurial spirit and proactive approach to problem-solving.
• You possess a deep-seated curiosity for exploring emerging technologies and implementing best practices to overcome challenges.
• Your self-motivation and accountability drive you to take ownership of your work while actively contributing to the collective learning environment.

What are your daily responsibilities?

• Design, develop, and maintain robust data pipelines to facilitate the collection, processing, and transformation of data from diverse sources for analysis.
• Optimise data storage, retrieval, and processing mechanisms to ensure the scalability and efficiency of the analytics infrastructure.
• Collaborate closely with business stakeholders to discern their data needs and translate requirements into effective data analysis and visualisation solutions.
• Manage and enhance data models within the data lake and transformation layer.
• Create actionable data visualisations to empower Valenture stakeholders with insights for decision-making.
• Provide technical support for debugging, testing, and performance tuning of data assets, visualisation assets, and prediction assets.
• Identify and address data quality issues to uphold data integrity and consistency.
• Stay abreast of industry trends, tools, and technologies relevant to data engineering and analytics.

What Stack Will You Be Using?

• Snowflake
• dbt
• Fivetran
• Airbyte
• AWS
• Looker (LookML)
• Python
• Gitlab

Requirements

• Bachelor’s degree in Computer Science, Applied Mathematics, Statistics, Relevant Engineering Discipline, or Equivalent Practical Experience.
• Strong problem-solving skills and meticulous attention to detail.
• Excellent communication and teamwork abilities.
• Rapid adaptability to new technologies and methodologies.
• Proficiency in SQL and experience with relational databases (e.g., MySQL, PostgreSQL).
• Fundamental understanding of data warehousing concepts and ETL processes.
• Experience with Git and Git-based workflows.
• Prior exposure to data vaulting and dbt is advantageous.
• Familiarity with data visualisation tools (e.g., Looker, Tableau, Power BI).
• Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud) is beneficial.
• Understanding of data science libraries in Python (e.g., pandas, numpy, scikit-learn, seaborn) is a plus.