Background

CloudFactory is changing the way the world works by providing an on-demand, digital workforce for scaling critical business processes in the cloud. We’re also on a mission to create meaningful work for as many people as possible.

Role Summary

As a Data Engineer, you will build and maintain the data pipelines and models that power CloudFactory's reporting and analytics. You will work with tools such as Fivetran, DBT, Snowflake, and Python to extract, transform, and model data, while ensuring data quality, security, and governance standards are consistently met. This is a great opportunity to grow your data engineering expertise within a mission-driven, fast-scaling organization.

Please note: This is a full-time, fixed-term employee position with an expected duration of 6 months.

Responsibilities:

Data Pipeline Development

• Develop data pipelines in Fivetran to extract data from common data sources.
• Write Python scripts, using libraries such as Pandas, for data cleaning and transformation.
• Create data models in DBT with transformations and joins between tables.

Data Quality and Governance

• Implement data quality checks in DBT and Snowflake to identify and address data quality issues.
• Follow established data governance practices, including access controls and documentation procedures.
• Monitor data pipelines for errors or inconsistencies, reporting issues to senior engineers.

Data Modelling and Design

• Design and document conceptual and logical data models for well-defined datasets, considering star schema or data vault principles.
• Apply data normalization techniques and select appropriate data types based on data characteristics.
• Collaborate with stakeholders to understand their data needs and identify potential model improvements.

Data Visualization Support

• Create data visualizations in QuickSight or Tableau to explore and communicate data insights.
• Select appropriate chart types and apply dashboard design principles for effective communication.

Delivery And Testing

• Take ownership of designing and implementing moderately complex data engineering tasks, identifying dependencies and risks during planning.
• Write integration tests to verify how code interacts with other parts of the data pipeline.

Data Security And Compliance

• Adhere to established data security and compliance protocols while handling data.
• Follow data access control procedures and complete required data security and compliance training.

Requirements

Must-have skills (required)

• Good understanding of data engineering concepts, data transformation techniques, and tools such as Fivetran, DBT, Snowflake, and QuickSight or Tableau.
• Proficient in Python, including libraries such as Pandas, for data cleaning and transformation.
• Experience building and maintaining data pipelines from common data sources.
• Understanding of data modelling methodologies and normalization principles for data warehousing.
• Experience implementing data quality checks and following data governance practices.
• Familiarity with data visualization tools and best practices for effective dashboards.
• Strong SQL skills for querying and transforming data.
• Good communication skills, able to collaborate with stakeholders on data requirements.

Academic And Professional Requirements

• Bachelor's degree in Computer Science, Data Engineering, or a related field, or equivalent practical experience.
• 2–4 years of experience in data engineering or a related role.

Nice-to-have skills (preferred)

• Experience with Snowflake performance optimization.
• Exposure to workflow orchestration tools.
• Familiarity with data governance frameworks.

Benefits

• Great Mission and Culture
• Meaningful Work
• Market competitive salary
• Quarterly variable compensation
• Comprehensive medical cover
• Group life insurance
• Personal development and growth opportunities
• Office snacks and lunch
• Periodic team building and social events

• Develop data pipelines in Fivetran to extract data from common data sources.
• Write Python scripts, using libraries such as Pandas, for data cleaning and transformation.
• Create data models in DBT with transformations and joins between tables.
• Implement data quality checks in DBT and Snowflake to identify and address data quality issues.
• Follow established data governance practices, including access controls and documentation procedures.
• Monitor data pipelines for errors or inconsistencies, reporting issues to senior engineers.
• Design and document conceptual and logical data models for well-defined datasets, considering star schema or data vault principles.
• Apply data normalization techniques and select appropriate data types based on data characteristics.
• Collaborate with stakeholders to understand their data needs and identify potential model improvements.
• Create data visualizations in QuickSight or Tableau to explore and communicate data insights.
• Select appropriate chart types and apply dashboard design principles for effective communication.
• Take ownership of designing and implementing moderately complex data engineering tasks, identifying dependencies and risks during planning.
• Write integration tests to verify how code interacts with other parts of the data pipeline.
• Adhere to established data security and compliance protocols while handling data.
• Follow data access control procedures and complete required data security and compliance training.

• Good understanding of data engineering concepts, data transformation techniques, and tools such as Fivetran, DBT, Snowflake, and QuickSight or Tableau.
• Proficient in Python, including libraries such as Pandas, for data cleaning and transformation.
• Experience building and maintaining data pipelines from common data sources.
• Understanding of data modelling methodologies and normalization principles for data warehousing.
• Experience implementing data quality checks and following data governance practices.
• Familiarity with data visualization tools and best practices for effective dashboards.
• Strong SQL skills for querying and transforming data.
• Good communication skills, able to collaborate with stakeholders on data requirements.
• Experience with Snowflake performance optimization.
• Exposure to workflow orchestration tools.
• Familiarity with data governance frameworks.

• Bachelor's degree in Computer Science, Data Engineering, or a related field, or equivalent practical experience.