Data Engineer

• Code contributing member of an Agile team, working to deliver sprint goals
• Demonstrating technical knowledge and expertise in software development, including programming languages, frameworks, and best practices
• Actively contributes to the implementation of features and technical solutions
• Write clean, efficient, and maintainable code that meets the highest standards of quality
• Collaborate with other Engineers to define and evolve the overall system architecture and design
• Provide guidance on scalable, robust, and efficient solutions that align with business requirements and industry best practices
• Offer expert engineering guidance and support to multiple teams, helping them overcome technical challenges, make informed decisions, and deliver high-quality software solutions
• Foster a culture of technical excellence and continuous improvement
• Stay up to date with emerging technologies, tools, and industry trends
• Evaluate their potential impact on the organization and provide recommendations for technology adoption and innovation

• 0-2+ years’ experience of implementing data-intensive solutions using agile methodologies
• Proficient in one or more programming languages commonly used in data engineering such as Python, Java, or Scala
• Multiple years of experience with software engineering best practices (unit testing, automation, design patterns, peer review, etc.)
• Strong proficiency in working with relational databases and using SQL for data querying, transformation, and manipulation
• Clear understanding of Data Structures and Object Oriented Principles
• Experience of modelling data for analytical consumers
• Ability to automate and streamline the build, test and deployment of data pipelines
• Proven experience of providing technical vision and guidance to a data team
• Thrives in a dynamic environment, capable of managing multiple tasks simultaneously while maintaining a high standard of work
• BA/BS degree or equivalent work experience

• Experience with Hadoop for data storage and processing is valuable, as is exposure to modern data platforms such as Snowflake and Databricks
• Multiple years of experience architecting and building horizontally scalable, highly available, highly resilient, and low latency applications
• Multiple years of experience with Cloud-native development and Container Orchestration tools (Serverless, Docker, Kubernetes, OpenShift, etc.)
• Familiarity with open-source data engineering tools and frameworks (e.g. Spark, Kafka, Beam, Flink, Trino, Airflow, DBT) is a valuable asset
• Exposure to a range of table and file formats including Iceberg, Hive, Avro, Parquet and JSON
• Experience in cloud native technologies and patterns (AWS, Google Cloud)
• Exposure to Infrastructure as Code tools (i.e., Terraform, Cloudformation, etc.)
• Experience of driving and/or influencing the data strategy of your team or organization

Global benefits designed to support well-being, growth, and work-life balance