Job Description

About the Role:

We are looking for an experienced

Senior Data Engineer

with strong hands-on expertise in

Azure Data Services

, particularly

Azure Databricks

. The ideal candidate will be responsible for building robust, scalable, and high-performance data solutions to support business analytics and insights.

Databricks certification

is highly preferred.

Key Responsibilities:

Design, develop, and maintain

data pipelines

and

ETL/ELT workflows

using

Azure Data Factory

and

Azure Databricks

. Build and optimize

data lake

and

data warehouse

architectures on Azure. Implement efficient

data ingestion

,

transformation

, and

cleansing

processes from diverse sources. Develop and tune

PySpark/SparkSQL

code for large-scale data processing. Ensure

data quality

,

lineage

, and

security compliance

across all layers. Collaborate with data analysts, scientists, and business stakeholders to enable data-driven decision-making. Optimize cost and performance of data solutions in the

Azure cloud environment

.

Technical Skills Required:

Mandatory:

Azure Databricks (

hands-on, advanced level

) - Databricks Certification preferred*
Azure Data Factory (ADF) Azure Data Lake Storage (ADLS) Azure Synapse Analytics / SQL Data Warehouse Proficiency in

PySpark

,

SQL

, and data modeling

Good to Have:

Experience with

Delta Lake

,

Power BI

, or

Azure DevOps CI/CD pipelines

Scripting experience in

Python

or

Scala

Exposure to

data governance, monitoring, and optimization

Qualifications:

Bachelor's or Master's in Computer Science, Information Technology, or a related field. 4-7 years of proven experience in

data engineering

, specifically within the

Azure ecosystem

.

Azure Databricks certification

is a strong plus.

What We're Looking For:

Excellent analytical and problem-solving mindset. Strong communication and collaboration skills. Self-motivated and capable of delivering in fast-paced environments.

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