Design, develop, and maintain
ETL/ELT
pipelines on
Azure Data Platform
.
Implement
big data solutions
using
Azure Databricks and PySpark
.
Optimize and enhance data processing using
PySpark, Python, and SQL
.
Develop
data models and data transformations
for analytical and reporting solutions.
Work with structured and unstructured datasets, ensuring data quality and integrity.
Design and implement
Azure Data Lake Storage (ADLS) and Delta Lake solutions
.
Collaborate with
cross-functional teams
(data scientists, analysts, business users) to define and execute data strategies.
Monitor
Azure Data Factory (ADF) workflows
, troubleshoot failures, and optimize performance.
Ensure security, governance, and compliance best practices within the Azure data ecosystem.
Participate in
code reviews
, ensure best coding practices, and maintain documentation.

Required Skills:

5+ years of experience
in data engineering, with a strong focus on
Azure cloud solutions
.
Proficiency in
Azure Databricks
and
PySpark
for big data processing.
Strong expertise in
SQL
for data manipulation, optimization, and performance tuning.
Hands-on experience with
Python
for data processing and automation.
Experience with
ETL development
using
Azure Data Factory (ADF)
and/or other ETL tools.
Knowledge of
Delta Lake architecture
and data lake best practices.
Experience with
Azure Data Lake Storage (ADLS), Synapse Analytics, and Cosmos DB
(optional but preferred).
Strong understanding of
data warehousing, data modeling, and performance optimization
.
Experience with
CI/CD pipelines
, version control (Git), and DevOps for data engineering.
Knowledge of
data governance, security, and compliance best practices
.

Preferred candidate profile

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