Lead Data Engineer-Canberra -Hybrid

IT Alliance; Canberra; Hybrid; AUD 130.000 - 190.000; Vollzeit

Zusammenfassung

IT Alliance is seeking a Lead Data Engineer for Canberra to work across data and analytics platforms. You will develop ETL/ELT and data visualisation pipelines using Azure Databricks, Data Factory, SQL Server and related tools.

The role focuses on data movement, transformation, and data visualisation to support decision making, leveraging modern cloud technologies and agile delivery.

Qualifikationen

• Demonstrated ETL/ELT experience for complex data pipelines.
• Experience with cloud data platforms and analytics tools.
• Strong communication and collaboration skills.

Aufgaben

• Participate in design, development and testing of data pipelines.
• Develop data ingestion and transformation solutions for analytics.
• Create visualisations and data products for decision making.
• Collaborate in an agile team across departments.

Kenntnisse

ETL/ELT development

Data visualisation

Azure Databricks

SQL Server

Data Factory

Cloud data movement

Agile teamwork

Effective communication

Tools

Azure Databricks

Power BI

SQL Server Integration Services

DevOps

Visual Studio

Jobbeschreibung

One of our federal govt clients is seeking to engage Lead Data Engineer for Canberra location

• Extension term details -24 months
• Location of work - ACT
• Working arrangements -Hybrid

One of our federal govt clients is seeking to engage Lead Data Engineer for Canberra location

• Initial contract duration- 12 months
• Extension term details -24 months
• Experience level EL1 equivalent
• Location of work - ACT
• Working arrangements -Hybrid

Job details

Our client is looking for a Data Engineer who can work across its data and analytics platforms. We are seeking candidates with strong experience in developing Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes, and /or the development of data products and complex data visualisations.

The role will be responsible for design, development and testing activities across several data movement, data transformation, and data visualisation processes . The data movement and transformation processes focus on the preparation of data for use in decision making processes across the department, utilising modern cloud technology (Azure & Databricks) to enable operational analytics use cases.

Key duties and responsibilities

Responsibilities include, but not limited to:

• Be responsive, flexible, and work collaboratively as part of an agile team.
• Strong relationship building, and negotiation skills.
• Strong written and oral communication skills.
• Creating and maintaining automated ingest and transformation patterns and frameworks.
• Designing, building and maintaining data ingest and transformation solutions to meet current and emerging needs.
• Assisting project teams achieve objectives that align with departmental, divisional, and program priorities.
• Supporting data engineers in delivery teams, through regular quality reviews and constructive feedback on utilising data assets to produce quality data products.

The successful candidate will require experience with the following techniques and technologies:

• Data Integration - Data Factory, SQL Server Integration Services and/or Databricks
• Data Store - SQL Server and/or Data Lake Storage
• Analytics - Azure Databricks, Azure Machine Learning, ArcGIS Enterprise
• Development tools – DevOps, Visual Studio
• Data technology solutions – sourcing (Oracle, Ingres, Azure, SQL Server), automated ingestion
• Data Preparation
• Transformation of data into formats tailored for advanced analytics and AI use cases – Parquet and/or Delta
• Data Visualisation
• Analyse and interpret complex data sets, and to identify trends and patterns.
• Design principles to create appropriate visualisations for target audience.
• Visualisation tools - Power BI.

Weighting

• 1.Demonstrated experience developing ETL/ELT processes for complex and/or large data movement, transformation and/or visualisations, particularly in a cloud environment.
• Weighting:50%

• 2. Experience preparing data optimised for query performance in cloud computed engines. E.g.

  • Distributed computing engines (Spark)
  • Graph Databases
  • Azure SQL
• Weighting:25%
• 3.Experience working with Engineering, Storage and Analytics services in cloud infrastructure.
• Weighting:25%

Desirable criteria

• 1.Experience working with Azure Data Factory and Databricks.
• 2.Experience/Knowledge of working with Data Lake and Lakehouses.