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
