Data Engineer
1 week ago
About the Role
We are looking for a
Data Engineer
with strong experience in
Spark (PySpark)
,
SQL
, and
data pipeline architecture
. You will play a critical role in designing, building, and optimizing data workflows that enable scalable analytics and real-time insights. The ideal candidate is hands-on, detail-oriented, and passionate about crafting reliable data solutions, while collaborating with cross-functional teams.
Responsibilities
- Design and architect
scalable and efficient data pipelines
for batch and real-time processing. - Develop and optimize solutions using
Spark (PySpark)
and
SQL
. - Ensure data pipelines are
reliable, maintainable, and well-tested
. - Work with stakeholders to understand business requirements and translate them into
data-driven solutions
. - Collaborate with cross-functional teams to ensure
data quality, availability, and performance
. - Stay updated with
emerging data engineering tools and practices
.
Must-Have Skills
- Strong expertise in
Spark (PySpark)
. - Proficiency in
SQL
(query optimization, performance tuning, complex joins). - Hands-on experience in
designing and architecting data pipelines
. - Excellent
communication and collaboration skills
.
Good to Have
- Experience with
data streaming platforms
(Kafka, Kinesis, etc.). - Proficiency in
Python
for data engineering tasks. - Exposure to
Databricks
and
Azure cloud
services. - Knowledge of
HTAP systems, Debezium, 3PL/logistics domain
(having most of this mentioned skills would be great) - Familiarity with
orchestration frameworks
such as
Apache Airflow
or
Apache NiFi
.
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