
Pyspark Data Engineer
3 days ago
We are looking for a skilled
Data Engineer
with hands-on experience in
PySpark
and
Databricks
to design, develop, and optimize large-scale data pipelines. The ideal candidate should have strong problem-solving skills, experience working in cloud-based environments, and the ability to collaborate effectively with cross-functional teams.
Key Responsibilities:
- Develop and maintain
ETL/ELT pipelines
using
PySpark
on Databricks. - Optimize data processing workflows for
performance and scalability
. - Work with structured, semi-structured, and unstructured data from multiple sources.
- Collaborate with data scientists, analysts, and business teams to deliver
clean, reliable datasets
. - Implement
data quality checks, validations, and monitoring
. - Support migration of existing pipelines to
cloud platforms
(Azure/AWS/GCP). - Document technical solutions, workflows, and best practices.
Required Skills:
- 3–5 years
of experience in data engineering roles. - Strong expertise in
PySpark
(DataFrames, RDDs, Spark SQL). - Hands-on experience with
Databricks
(Delta Lake, Workflows, Jobs, Clusters). - Solid understanding of
data warehousing concepts
and
SQL
. - Experience with
cloud platforms
(Azure Data Lake, AWS S3, or GCP BigQuery). - Familiarity with
CI/CD pipelines
and version control (Git). - Good understanding of
performance tuning and optimization
in Spark. - Strong problem-solving and debugging skills.
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