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Senior Data Engineer

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Hybrid

Senior Data Engineer

Wissen Technology

Senior Data Engineer

Skills

SQL QueriesData MiningPythonGitData AnalysisPySpark

1 month ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

11 September 2026

What they need


Role & responsibilities

  • Design, develop, and maintain scalable data pipelines and ETL/ELT workflows using Python and PySpark.
  • Develop efficient PySpark applications for processing large volumes of structured and semi-structured data.
  • Write optimized Python scripts and modules for data processing, automation, and transformation.
  • Develop complex SQL queries for data extraction, transformation, validation, and analysis.
  • Perform data cleansing, transformation, aggregation, and validation across large datasets.
  • Optimize PySpark jobs for performance, scalability, memory utilization, and execution time.
  • Work with distributed computing concepts such as Spark architecture, DataFrames, RDDs, partitions, joins, caching, and transformations/actions.
  • Build and maintain robust and reusable data engineering frameworks.
  • Troubleshoot data pipeline failures and resolve performance and data-quality issues.
  • Implement data validation, error handling, logging, and monitoring mechanisms.
  • Collaborate with Data Scientists, Analytics teams, Software Engineers, and Business stakeholders.
  • Participate in code reviews and follow coding, testing, and documentation best practices.
  • Contribute to the design and implementation of scalable cloud-based data solutions.

Preferred candidate profile

  • 7+ years of overall experience in Data Engineering / Big Data / Python development.
  • Strong hands-on experience with Python.
  • Strong hands-on experience with PySpark / Apache Spark.
  • Strong proficiency in SQL and relational databases.
  • Good understanding of ETL/ELT concepts and data pipeline development.
  • Experience working with large datasets and distributed data processing.
  • Strong understanding of Spark DataFrames, transformations, actions, joins, partitioning, caching, and optimization techniques.
  • Experience with data formats such as JSON, CSV, Parquet, and Avro.
  • Good understanding of data structures, algorithms, and object-oriented programming in Python.
  • Experience with Git/version control and software development best practices.
  • Strong debugging, analytical, and problem-solving skills.

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