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.