Azure Data Engineer
7 days ago
We are urgently seeking a highly skilled and experienced
Azure Databricks Data Engineer
to join our team in Sydney. This is a critical role for our data engineering function, focused on building robust, scalable, and efficient data solutions within the Azure cloud environment.
If you have a passion for building complex data pipelines and thrive on solving large-scale data challenges, we want to hear from you. This contract offers the opportunity to work on impactful projects with a high chance of long-term engagement.
Key Responsibilities:
- Design & Development:
Architect, develop, and optimize data pipelines and ETL/ELT processes using modern tools like
Azure Data Factory
,
Azure Synapse Analytics
, and primarily
Azure Databricks
. - Data Transformation:
Work with large volumes of structured and unstructured data to build and maintain data lakes, data warehouses, and real-time streaming solutions. - Performance & Optimization:
Utilize
Apache Spark
within Databricks to handle large-scale data processing and optimize the performance and cost of data workflows in Azure. - Collaboration:
Partner closely with data scientists, business analysts, and key stakeholders to understand data requirements and deliver solutions that meet business objectives. - Data Governance & Security:
Implement and enforce best practices in data quality, security, and governance using tools such as
Azure Purview
,
Azure Key Vault
, and Role-Based Access Control (RBAC).
Required Skills & Qualifications:
- Experience:
A minimum of
4 years
of hands-on experience as a Data Engineer or in a similar role. - Databricks Expertise:
Strong, demonstrable experience with
Azure Databricks
and deep knowledge of
Apache Spark
. - Technical Proficiency:
Expert-level skills in
Python
,
PySpark
, and
SQL
are essential. - Azure Stack:
In-depth knowledge of core Azure data services, including
Azure Data Lake Storage
,
Azure Blob Storage
, and
Azure Data Factory
. - Data Architecture:
Solid understanding of
Delta Lake architecture
and modern
data lakehouse
concepts. - DevOps:
Familiarity with CI/CD pipelines and DevOps practices within the Azure ecosystem (e.g., using
Azure DevOps
). - Foundational Knowledge:
A strong grasp of data modeling techniques, performance tuning, and cloud security principles.
If you are an experienced data engineer looking for a challenging and impactful role, we'd love to hear from you.
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