Senior Data Engineer
3 semanas atrás
Data Engineer Role Overview
At Planet, we're transforming payments by putting customer experience first. We offer integrated solutions that include payment processing, VAT refunds, dynamic currency conversion, and management services for merchants in the Retail and Hospitality sectors worldwide.
As a Data Engineer, you'll play a key role in building and maintaining our data infrastructure, with a focus on Snowflake, Fivetran, and dbt. You'll be responsible for designing, developing, and optimising data pipelines that power our analytics and business intelligence.
Key Responsibilities:
• Design and develop data pipelines using Fivetran for data ingestion, ensuring smooth integration of multiple data sources into Snowflake.
• Manage the administration, maintenance, and optimisation of our Snowflake data warehouse, ensuring data is structured for efficient querying and analysis.
• Utilise dbt to create data models, transforming raw data into clean, well-structured datasets ready for analytics and reporting.
• Develop and optimise ETL/ELT processes to ensure timely and accurate data ingestion and transformation, with a focus on automation and efficiency.
• Implement monitoring and testing frameworks to ensure data quality, reliability, and pipeline performance.
• Collaborate with data analysts, data scientists, and business stakeholders to understand their data needs and deliver solutions that support business objectives.
Requirements:
• Proficient with Snowflake, including experience in managing and optimising Snowflake as a data warehouse.
• Expert in Fivetran, with hands-on experience using Fivetran for data ingestion, integrating multiple data sources seamlessly.
• Skilled in dbt, with a strong knowledge of dbt for data transformation, including a track record of building robust and scalable data models.
• Advanced SQL skills for querying, transforming, and analysing data across databases and data warehouses.
• Experience with cloud platforms (AWS, Azure, GCP) and their data services, including knowledge of data governance and security best practices.
• Familiarity with real-time data processing tools (Kafka, Kinesis).
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