to join our cloud data engineering team. In this role, you will be responsible for building, optimizing, and maintaining data pipelines and processing systems on the
Azure and Databricks ecosystem
. The ideal candidate has strong hands-on experience with
Python, SQL, PySpark
, and
Azure SQL environments
, as well as a solid understanding of
ETL/ELT design patterns
,
data modeling
, and
cloud performance optimization
.
You will collaborate with architects, analysts, and data scientists to ensure data is efficiently transformed, processed, and made available for analytics, reporting, and machine learning use cases.
###
Key Responsibilities
Develop and maintain
scalable, high-performance data pipelines
using
Databricks (Python, SQL, PySpark)
.
Design and implement
ETL/ELT workflows
to move and transform data across Azure data platforms.
Work with
Azure SQL Server
environments, including
Managed Instances
,
Azure SQL Databases
, and
SQL Server VMs
to manage data ingestion and integration.
Design
data models
and implement best practices for schema design, data quality, and lineage tracking.
Use
Docker
and
Azure Kubernetes Service (AKS)
to automate, containerize, and deploy scalable data processing workloads.
Optimize
Databricks cluster configurations
,
SQL queries
, and
data transformation logic
for cost and performance efficiency.
Collaborate with data architects and business stakeholders to design and implement robust
data architecture solutions
.
Support
performance tuning, troubleshooting
, and proactive monitoring of data pipelines.
Contribute to
CI/CD processes
and data pipeline automation to enhance deployment efficiency.
Required Skills
DEVOPS ENGINEER
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