Job Description
Job Details:
Job title: Data Engineer
Location: Bengaluru, India
Long-term contract
Job Overview:
We are seeking a Data Engineer with 3–5 years of hands-on experience in Spark and Spark SQL, strong SQL expertise, and solid batch processing experience.
Must have skills – Spark, Spark SQL, at least 5-8 years of working experience with Spark. Very Strong SQL; Batch Exp is a must-have. Good Project Experience.
Python is a plus not a must-have.
Data Engineer Job Description:
5-8 years of hands-on experience with Apache Spark (especially Spark SQL and batch processing).
Strong SQL expertise — ability to write efficient, optimized, and complex SQL queries for large datasets.
Solid understanding of data pipeline fundamentals, including ingestion, transformation, and loading (ETL/ELT) processes.
Must have experience with batch data processing (scheduling, dependencies, failure recovery, performance tuning).
Knowledge of data warehousing concepts and familiarity with relational databases.
Experience working with structured and semi-structured data (CSV, Parquet, JSON, etc.).
Strong problem-solving and debugging skills, particularly around pipeline performance and data quality.
Thanks
Neha Singh
Whats App:
Job title: Data Engineer
Location: Bengaluru, India
Long-term contract
Job Overview:
We are seeking a Data Engineer with 3–5 years of hands-on experience in Spark and Spark SQL, strong SQL expertise, and solid batch processing experience.
Must have skills – Spark, Spark SQL, at least 5-8 years of working experience with Spark. Very Strong SQL; Batch Exp is a must-have. Good Project Experience.
Python is a plus not a must-have.
Data Engineer Job Description:
5-8 years of hands-on experience with Apache Spark (especially Spark SQL and batch processing).
Strong SQL expertise — ability to write efficient, optimized, and complex SQL queries for large datasets.
Solid understanding of data pipeline fundamentals, including ingestion, transformation, and loading (ETL/ELT) processes.
Must have experience with batch data processing (scheduling, dependencies, failure recovery, performance tuning).
Knowledge of data warehousing concepts and familiarity with relational databases.
Experience working with structured and semi-structured data (CSV, Parquet, JSON, etc.).
Strong problem-solving and debugging skills, particularly around pipeline performance and data quality.
Thanks
Neha Singh
Whats App:
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