Senior Data Engineer

Responsibilities: • Support the business’s goal of democratisation of data and data products. • Drive audience and behavioural analytics, as well as key business metrics with associated dashboard and reporting. • Collaborate in partnership with diverse teams across organization such as product engineering, data science and business stakeholder teams to successfully deliver business outcomes. • Work with a mix of cloud infrastructure and open-source technologies to build, scale, and maintain data workloads. • Work with media industry data practitioners in domains across sales, marketing and advertising, engineering, corporate and organization publications to deliver innovative and game changing data products and use cases. • Work to design, build and implement data workloads across both high and low volume and velocity of data to support business use cases. • Implement cloud-based scalable and reliable data pipelines at significant scale. • Implement reliable and redundant data workloads to provide accurate, easy-to-use and timely data to deliver positive business outcomes. • Build and maintain streaming and batch data pipelines. • Build and maintain transactional and analytical data schemas for data lake, data warehouse and data marts. • Implement Data Analytics and Business Intelligence frameworks to support Enterprise Data needs. • Adhere to Data Governance policies and implementation from collection to storage and activation of a broad range of data products. • Utilise data-related languages and frameworks such as Python, Spark, SQL, Hudi, Iceberg. • Propose Solutions for Data Pipelines, Data Schema and/or Business Intelligence Dashboards and Reports. • Adhere and have practised Agile Methodology such as Scrum. • Implement adhering to Master Data Management Best Practices and Principles. • Understand and Design Data Models following BI Best Practices such as Dimensional Modelling. Requirements: • At least 5 years of relevant hands-on experience in cloud-based data engineering, business analyst, or solution architect roles. • Experience in data-related infrastructure deployments using Terraform Cloud. • Experience in using Git for version and release management with knowledge in branching strategies. • Experience in AWS Data and Analytics services such as EMR, Glue, Lambda, Step Functions, Athena, Kinesis, or QuickSight. • Implementation Experience in Business Intelligence Platforms and Tools such as Tableau, QuickSight. • Experience in utilising query engines such as Presto on Data Lakes, Data Warehouses and Data Marts. • Good communication skills for Data and Analytics concepts and methodologies and how they are relevant to your stakeholders. #J-18808-Ljbffr