EXPERIENCE REQUIRED:

• Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience)
• 5 years of experience in a data engineering role
• Experience in designing and implementing data models for relational and non-relational databases
• Proficiency in languages commonly used in data engineering, specifically SQL and Python
• Familiarity with data warehouse concepts and technologies, particularly Google BigQuery. ( Experience with Amazon Redshift can also be considered)
• Understanding of a variety of databases including both SQL and NoSQL databases
• Hands-on experience with ETL tools and processes to move and transform data between systems
• Experience with Google Cloud Platform (GCP) is highly preferred.(Experience with other cloud platforms like AWS, Azure can be considered.)
• Familiarity with data pipeline scheduling tools like Apache Airflow
• Ability to design, build, and maintain data pipelines for efficient data flow and processing
• Understanding of data warehousing best practices and experience in organising and cleaning up messy data warehouses
• Proficient in using version control systems like Git
• Experience in a start-up or fast-paced, dynamic work environment.

ABOUT THE ROLE:

As a Senior Data Engineer at Geomiq, you will play a central role in shaping our data infrastructure and operations. Your primary focus will be on establishing a robust foundation that is not only fit for the current needs but also sustainable for future growth. You’ll be responsible for collecting data from various sources, ensuring its structure, and making it easily accessible for Business Intelligence and Data Science purposes.

MAIN RESPONSIBILITIES:

• Data Infrastructure Ownership: Take ownership of the end-to-end data infrastructure, from aggregating data to designing, building and maintaining scalable and efficient pipelines.
• Cross-functional data collaboration: Collaborate with data scientists, analysts, and product teams to understand their data requirements and deliver solutions that meet their needs.
• Data Warehousing: Design, implement and optimise data warehousing solutions to support efficient data storage, retrieval and analysis, as well as working with 3rd party tools, such as Hubspot and Mixpanel.
• Continuous Improvement: Stay abreast of industry best practices, proactively identifying opportunities for improvement in data processes.