Data Platform Engineer

Summary

Join Vector, a company modernizing its electricity distribution network and embedding smart technologies, as a Data Platform Engineer. You will design, implement, and support cloud-based data solutions, working within an Agile DevOps team. Responsibilities include building and maintaining data platforms, integrating machine learning models, and providing DevOps support. The ideal candidate has at least 3 years of experience in platform or data engineering, proficiency in data engineering concepts, and hands-on experience with AWS data lake technologies and various data tools. Vector offers a collaborative environment, professional development opportunities, flexible work options, comprehensive health and wellbeing support, and great family-focused benefits.

Requirements

• At least 3 years of professional experience as a Platform Engineer or Data Engineer, with a strong foundation in designing and implementing scalable data solutions
• Proficiency in data engineering concepts, tools, and best practices, including data modeling, ETL processes, and pipeline architecture
• Hands-on experience with: AWS data lake technologies (IAM, S3, EC2)
• Data ingestion tools (Fivetran, AWS Glue)
• Data transformation tools (Coalesce, DBT)
• Snowflake cloud data platform
• CI/CD pipeline development
• Working knowledge of BDD and TDD, enabling the development of reliable and testable data solutions
• Experience with Agile methodologies and a DevOps culture, fostering collaboration and continuous improvement
• Strong interpersonal skills, with a proven ability to build and maintain effective relationships with diverse stakeholders through clear and empathetic communication
• Adaptability in dynamic matrix environments, effectively collaborating across cross-functional teams and adjusting to evolving industry trends, priorities, tools, processes and workflows

Responsibilities

• Design and implement data flow and processing pipelines using AWS Glue, Lambda, and Fivetran
• Build and maintain CI/CD pipelines in AWS cloud
• Integrate machine learning models using services like AWS SageMaker
• Provide DevOps support for our Enterprise Data Warehouse and BI & Analytics platform
• Design and implement unit tests for data processing pipelines
• Contribute to technical leadership and architecture decisions

Benefits

• Work in a collaborative and inclusive environment with a strong focus on professional development
• Enjoy flexibility, including work-from-home options and flexible hours
• Comprehensive health and wellbeing support
• Great benefits that reflect the importance of family