Data Engineer

Mane Consulting; Canberra; On-site; AUD 110,000 - 160,000; Full time

Job summary

Mane Consulting is seeking a Data Engineer to help deliver our data roadmap and transform data into actionable insights from our Canberra base. You will build scalable pipelines in Azure, enabling ingestion, transformation and loading of data across sources into our data ecosystem.

You will work with Azure Data Factory, Databricks, Synapse, Purview, and Power BI to enable advanced analytics and trusted data products for the business.

Qualifications

• Experience in data warehousing, ETL/ELT, and dimensional data modeling.
• Hands-on with Azure data and analytics services such as Data Factory, Databricks, Synapse.
• Strong SQL skills and experience with Power BI for data visualization.
• Excellent communication and ability to translate business requirements.

Responsibilities

• Create and manage data pipelines for ETL/ELT ingestion into Azure data ecosystem.
• The Data Engineer must understand advanced analytics at scale with Purview, Synapse Analytics, and Power BI.
• Proficient in Azure Data Factory, Databricks, Synapse, and other Azure services to build scalable data solutions.
• Data Modeling: design efficient data models supporting analytical and operational workloads.
• Optimization and Performance Tuning: optimize storage, indexing, and query performance.

Skills

Data warehousing

ETL/ELT

Data modeling

T-SQL

SQL Server

PySpark

Databricks

Power BI

Azure Synapse Analytics

Azure Data Factory

Delta Lake

Purview

Tools

Azure Data Factory

Azure Databricks

Delta Lake

Azure Synapse Analytics

Power BI

Azure Purview

Azure Stream Analytics

Azure Data Lake Storage

Job description

At this industry disrupter you will have the rare opportunity to see how your work impacts the trajectory of a rapid-growth company. They are looking for a Data Engineer to help deliver on the strategic data roadmap that will quickly evolve the maturity of the business. this organisations wants someone with technical and communication skills, who is hungry to have an impact, and is not satisfied with mediocrity.

Do you love data and data pipelines? Does your brain wrangle data in your sleep? Do you like to use and deliver data in a meaningful way?

Responsibilities:

• Create and manage data pipelines that enable the ingestion, transformation, and loading (ETL/ELT) of data from various sources into our Azure data ecosystem.
• The Data Engineer must understand the methods and practices for performing advanced analytics at scale with Microsoft Purview, Microsoft Azure Synapse Analytics, and Microsoft Power BI.
• They must be proficient in the use of Azure Data Factory, Azure Synapse Analytics, Azure Stream Analytics, Azure Event Hubs, Azure Data Lake Storage, and Azure Databricks for creating data processing solutions.
• Leverage Microsoft Fabric for data integration, orchestration, and analytics, ensuring seamless data flow and accessibility across the organization.
• Utilize Azure Data Factory, Azure Databricks, Azure Synapse Analytics, and other Azure services to build scalable data solutions that meet business needs.
• Data Modeling: Design and implement efficient data models that support analytical and operational workloads, ensuring data quality, consistency, and performance.
• Optimization and Performance Tuning: Optimize data storage and retrieval processes, including indexing, partitioning, and query performance tuning, to ensure efficient use of resources.

To Succeed in this role you will you have:

• Data Engineering foundations: solid experience in data warehousing, ETL/ELT processes, and data modeling (dimensional, normalized)
• Previous hands‑on work with a broad range of Azure services related to Data and Analytics, including Azure Data Factory, Azure Databricks, Delta Lake, and Azure Synapse Analytics
• Proficient in T-SQL, SQL Server, Databricks, PySpark, SSRS, Power BI, and other related data tools and platforms
• Ability to extract and transform disparate data into actionable insights that will drive business decisions. Applying industry best practice transformation and modeling techniques – validating the output to ensure reliable and accurate results for consumption by downstream data teams, and end users.
• Drive development projects to evolve our platform and operations, leveraging the newest Microsoft technologies available to us.