About
We are seeking a
Senior Data Engineer
with strong hands-on experience in building AWS-based data pipelines. The ideal candidate will have deep expertise in Python, AWS Glue, PySpark, and cloud-native data engineering solutions. This role involves designing, developing, and maintaining scalable data pipelines and data warehouse solutions using AWS services.
Key Responsibilities: Build and maintain AWS-based data pipelines using
AWS Glue, PySpark, Python, and AWS Lambda Design and develop solutions for loading, organizing, and querying structured and semi-structured data in
AWS S3 Develop ETL processes using
AWS Glue ETL
and related AWS services Design and develop
data warehouse applications
using common standards and frameworks Work with AWS services such as
EMR, Redshift, Glue, and S3 Write and optimize
SQL queries
for analytical and reporting use cases Develop and maintain Python-based data processing code Use source code repositories (Git) and follow
CI/CD best practices Collaborate with cross-functional teams in an Agile delivery environment Ensure data quality, performance, and reliability across data pipelines Essential Skills:
Strong hands-on experience in
Python Hands-on experience with
AWS Glue
and AWS Cloud services Experience with
PySpark
for large-scale data processing Solid understanding of
NoSQL databases Strong SQL skills Knowledge of
AWS Lambda Basic knowledge of
Java Experience with
source code repositories (Git) Understanding of
CI/CD processes Skills (Mandatory):
Digital : Python Digital : Amazon Web Service (AWS) Cloud Computing Digital : NoSQL Digital : PySpark Experience Range in Required Skills:
8-10 years
of overall experience in Data Engineering Strong hands-on experience with AWS-based data engineering solutions Preferred / Desirable Skills:
Experience with
AWS EMR and Redshift Exposure to cloud-based data warehouse architectures Experience working in Agile/Scrum teams
Languages
- English
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