Data Engineer – Hadoop
1 day ago
We are seeking an experienced
Data Engineer
with strong expertise in the
Hadoop ecosystem
and
PySpark
. The ideal candidate should have a deep understanding of large-scale data processing, data pipelines, and automation using Python.
Key Responsibilities
- Design, develop, and optimize
data pipelines
using Hadoop and PySpark. - Work extensively on
HDFS, Hive, and Spark
for data ingestion, transformation, and analysis. - Implement
data models, ETL frameworks,
and performance tuning strategies. - Collaborate with data scientists and analysts to ensure data quality and accessibility.
- Develop
Python-based automation scripts
to streamline data engineering workflows. - Ensure data integrity, governance, and scalability across distributed systems.
Required Skills & Qualifications
- Strong hands-on experience
with the
Hadoop ecosystem
(HDFS, Hive, Spark, etc.) –
Mandatory - Proficiency in PySpark
for large-scale data processing –
Mandatory - Strong Python programming skills
for data manipulation and automation –
Mandatory - Experience with
ETL design, data modeling,
and
distributed computing frameworks - Familiarity with
big data storage formats
(Parquet, ORC, Avro, etc.) - Strong understanding of
SQL
and
data performance optimisation - Excellent problem-solving, debugging, and communication skills
Good to Have
- Exposure to
cloud data platforms
(AWS EMR, Azure HDInsight, or GCP Dataproc) - Experience with
Airflow, Kafka, or NiFi - Knowledge of
data security, governance, and CI/CD automation
How to Apply
Interested candidates can share their resume with the subject line
"Application – Data Engineer (Hadoop)"
at "" or apply directly via LinkedIn.
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