Practiv

Data Engineer

Sep 06, 2023

Sydney, New South Wales, Australia

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

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