Data Engineer — The Rocks, Sydney

As a Practiv Data Engineer you will join a team of passionate data-cloud technologists who help deliver end to end data engineering solutions for our customers from building data pipelines, warehousing the data and visualisation/presentation. Practiv Data Engineers understand both data pipeline development, operations and management as well as delivery of automated data solutions that are ready for production.What you’ll do: Solving our clients' most critical and difficult problems with advanced technologies. Being an integral part in helping to deliver Modern Data & Analytics solutions and help move our customers to the cloud Architecting data platforms to support our clients helping them fully leverage and organise their enterprise data Implementing data lakes as streaming platforms using the latest cloud and big data technologies Working with a fun, collaborative team where everyone can be themselves and are provided the opportunity to love their life What you’ll bring: Strong professional services background along with well-rounded experience to offer across different disciplines within data and analytics Experience with data services on any or all cloud platforms (Amazon Web Services, Azure, and Google Cloud) Proficiency in modern data architectures and relational database design and development Proficiency and hands-on experience with big data technologies Experience with agile engineering and product development lifecycles and ability to manage agile engineering client engagements Analytical approach to problem-solving; ability to use technology to solve business problems Requirements Strong SQL Skills 5 years of commercial database experience Experience with Cloud Data Warehouses (Amazon Redshift, Snowflake, Google BigQuery) Modern Data Workflows (Apache Airflow, dbt, Dagster) and experience with technologies such as Snowflake, Matillion, DBT, Tableau CRM, Fivetran etc Big Data Platforms (Apache Spark, Presto, Amazon EMR) Object Oriented Coding (Java, Python) NoSQL Databases (DynamoDB, Cosmos DB, MongoDB) Container Management Systems (Kubernetes, Amazon ECS) Artificial Intelligence / Machine Learning (Amazon Sagemaker, Azure ML Studio) Streaming Data Ingestion and Analytics (Amazon Kinesis, Apache Kafka) Visual Analytics (Tableau, PowerBI) Experience with object-oriented/object function scripting languages: SQL, Python, PySpark, Scala, etc